Theatre and Emotional Intelligence

A Quantitative Argument in Support of Drama Education

MMSS Senior Thesis

Richard Fromm 12 June 2015 Northwestern University Advisor: Diane Schanzenbach

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Table of Contents

1 Acknowledgements ................................................................................... 2

2 Abstract ..................................................................................................... 3

3 Introduction ............................................................................................... 4

4 Literature Review ..................................................................................... 10

5 Methodology ............................................................................................. 13

5.1 Experimental Design .................................................................... 13

5.2 The Test ........................................................................................ 15

6 Description of Data ................................................................................... 17

6.1 Format of the MSCEIT ................................................................. 17

6.2 MSCEIT Score Reporting ............................................................. 19

6.3 Scored Dataset .............................................................................. 21

7 Results ....................................................................................................... 22

7.1 Summary Statistics ....................................................................... 22

7.2 Paired t-tests .................................................................................. 23

8 Discussion ................................................................................................. 25

9 Conclusion ................................................................................................ 27

10 Appendix A: THEATRE 143-0 Syllabus ............................................... 28

11 Appendix B: Stata Output ....................................................................... 31

11.1 Total Scores ................................................................................ 31

11.2 Area Scores ................................................................................. 32

11.3 Branch Scores ............................................................................. 34

12 References ............................................................................................... 38

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1 Acknowledgements

There are so many people who made the completion of this thesis possible. I

would like to extend my sincerest gratitude to my advisor, Professor Diane

Schanzenbach, for encouraging me to pursue this crazy idea and for helping me fight all

of the battles that I couldn’t win alone. I would like to thank Professor Mary Poole, who

was gracious enough to lend me exorbitant amounts of her valuable time. Mary, your zeal

for teaching and great passion for theatre made this project what it is. I would like to give

a big thanks to Professor Shawn Douglass, who was kind enough to collaborate with me

on this project. I would also like to acknowledge Katie Dahlke for her assistance with

administering assessments and interpreting results. Additionally, I’d like to thank

everyone involved in the MMSS program. Thanks to Professor Joseph Ferrie for his

continued guidance throughout the thesis-writing process. Thanks to Professor William

Rogerson for his leadership and direction of the MMSS program. Thanks to Sarah Muir

Ferrer for her support of the program. I am also grateful for the Northwestern Office of

Undergraduate Research and for Mrs. Jeanette Dacey. Without their grants, I would have

nothing to write about. Each of these individuals and organizations helped me

immensely. My friends, family and colleagues all deserve thanks as well. Thank you all

for believing in this “theatre kid who can do math.”

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2 Abstract

In this paper, I investigate the potential link between theatre education and

emotional development. I describe a controlled experiment that I devised for testing the

effects of a drama course on emotional intelligence, as measured by the Mayer Salovey

Caruso Emotional Intelligence Test (MSCEIT).

I find that the connection between emotional intelligence and theatre isn’t as clear

as previous literature makes it out to be: One of my test groups increased their scores

after theatrical instruction – the other saw significant decreases in scores. My sample

sizes were very small, so the takeaways from my study should be considered exploratory,

at best.

My results indicate that further studies must be undertaken to develop a clearer,

more complete picture of how drama education affects students. With greater sample size

and some considerations for stress levels, class duration and structure, as well as teaching

style, a robust answer might be found to the question: Does participation in an acting

course increase one’s emotional intelligence?

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3 Introduction

Since the space race, our society has prioritized producing great scientists and

mathematicians. An emphasis on the STEM fields (science, technology, engineering and

mathematics) got us to the moon in 1969, and this emphasis continues to propel

American innovation today. But, analytical ability is only so important. People with

average IQs outperform those with the highest IQs 70% of the time (Bradberry, 2014).

How can this be? Studies of outstanding performers in organizations revealed the answer:

only one-third of the skills that set star performers apart come from technical expertise

and raw intelligence. The other two-thirds are based in something called emotional

intelligence (Goleman, 1998, p. 21).

Emotional intelligence (EI), at its core, is a metric of self-awareness, empathy and

emotional understanding. The term “emotional intelligence” started to appear in articles

during the early 1990s, when John D. Mayer and Peter Salovey introduced the concept.

They discussed emotional intelligence as “the subset of social intelligence that involves

the ability to monitor one’s own and others’ feelings and emotions, to discriminate

among them and to use this information to guide one’s own thinking and actions” (p.

189). Shortly after the term’s introduction, Daniel Goleman brought EI into the

mainstream with his book Emotional Intelligence: Why It Can Matter More than IQ

(Simmons, 2001). Goleman used a slightly different definition of EI. Since that time,

numerous authors have contributed their own spins on how EI should be defined. There’s

not a consensus as to which factors should be included in emotional intelligence. But,

according to Ciarrochi, Chan, and Caputi, “while the definitions of EI are often varied for

different researchers, they nevertheless tend to be complementary rather than

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contradictory” (2000, p. 540). In this study, we use the definition proposed by Mayer and

Salovey--an actual ability-based intelligence divided into four distinct branches:

(1) the ability to perceive emotions, (2) to access, generate, and use emotions so

as to assist thought, (3) to understand emotions and emotional knowledge, and (4)

to regulate emotions so as to promote emotional and intellectual growth. (Mayer

& Salovey, 1997, p. 8)

No matter which formal definition one chooses, emotional intelligence is

significant to personal and professional success. It’s “the single biggest predictor of

performance in the workplace and the strongest driver of leadership and personal

excellence,” according to Travis Bradberry (2014). The author claims that 90% of top

performers exhibit high EIs, compared to only 20% of bottom performers. So, while not

all emotionally intelligent people are star performers, a vast majority of star performers

are emotionally intelligent.

There are numerous studies that link EI with positive outcomes. Most of these

studies are within the management sciences (Law, 2004). Multiple studies find that high

EI managers have more engaged teams (Fariselli, 2013). They’re able to adjust more

easily to foreign assignments (Gabel, 2005), and they have stronger individual

performance levels (Bradberry, 2014). Research shows that emotionally intelligent

people are more satisfied in their daily lives. One of the most talked about studies in

emotional intelligence is the famous Marshmallow Test from Stanford University

(Mischel, 1989). In this experiment, researchers sat four year olds in an empty room with

a marshmallow. The children were given two options: eat the marshmallow, or wait

several minutes for the researcher to return with a second marshmallow. The children

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who were able to wait developed into drastically different adults than those with less

control. When the children were graduating high school, those who waited were more

stable, better liked, more motivated and more goal-oriented. On top of that, they had an

average SAT score 210 points higher (on the 1600 scale) than their impatient

counterparts. This experiment has been repeated, and the results are significant – EI is

critical to achievement.

That’s not to say that rational intelligence is unimportant. According to Goleman,

however, there is little variation in IQ amongst those in leadership positions. If one has an

IQ of 115 or 120, they can acquire a leadership position in their field. But, rational

intelligence is thought by most to be innate. That’s not the case with emotional

intelligence. Scholars agree that emotional intelligence can be consciously developed.

There is so much to gain from increasing EI that employers are placing significant value

on emotional intelligence training and emotional development seminars.

Psychologists and education reformers are jumping on the EI bandwagon as well.

Specialists have created social-emotional learning (S.E.L.) programs to try to combat

school violence, bullying and teen suicide. While there are many such S.E.L. programs,

they share a similar foundation. In the programs, students are asked to share their

emotions, comment on personal experiences, or discuss potential reactions to

hypothetical scenarios. Many of these programs are expensive and require extensive

training for teachers and faculty. With little evidence backing each unique program,

support behind S.E.L. programs has been slow to accumulate. But, schools across the

U.S. are beginning to implement them. In 2003, Illinois passed a bill making S.E.L. a part

of the schooling curriculum. And the move may pay off for Illinois students. Initial

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studies of S.E.L. are promising. One study found that preschoolers who had even a single

year of S.E.L. programming continued to perform better two years later. Another study

found that K-12 students who received S.E.L. instruction scored an average of 11

percentile points higher on standardized achievement tests (Kahn, 2013). But, more

studies need to be done. According to Caruso, who has coauthored many emotional

intelligence papers with Mayer and Salovey, “[S.E.L.] is a big messy field, with a lot of

promises, but very little data” (Kahn, 2013, p. 7).

With so much uncertainty about S.E.L. programs, I began to think of other ways

that emotional intelligence might be taught. Studies show that emotional intelligence

develops with age (Goleman, 1998, p. 24). This is intuitive. As we mature, we become

more self-aware and we are also exposed to a breadth of scenarios that build our social

knowledgebase. So, one idea to make people more emotionally intelligent was to

magically make them older. I had no interest in inventing a machine to rapidly age

students, and I have an inkling that the demand for such a machine would be low. But, I

thought to myself: How can educators expose students to a wide variety of life

experiences? The answer came easily – the theatre arts. Theatre programs might hold the

key to providing emotional learning, without an expensive and complicated S.E.L.

program.

So much of the practice of theatre is associated with emotional intelligence.

Theatre challenges students to better know themselves and their range of emotions.

Improvisation requires a willingness to listen, to accept change, and to say yes to new

possibilities. Acting forces students to put themselves into unfamiliar situations, to

imagine themselves as different people, as animals, or even objects. Discussions

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surrounding these scenes could potentially be an environment for emotional

development. So, I hypothesize that the theatre arts are a form of EI practice.

And I’m not the first to have this thought. The Second City, an improvisational

comedy enterprise based in Chicago, offers corporate training modules in the form of

Second City Works. Kelly Leonard and Tom Yorton, a duo from the company, recently

published Yes, And, a book about fostering adaptable leadership within organizations.

Jude Treder-Wolff, a creative arts psychotherapist, more explicitly discussed the links

between EI and improvisation. “It was clear to me that the mind and skill set [Goleman]

associates with emotional intelligence are integral to the philosophy and practice of

improvisation” (Boynton, 2013). Psychotherapists have also discussed the links between

emotion and theatre in a wider sense. Siobhan Fink proposed a model for the comparison

of various approaches to the management of emotion within and across the disciplines of

psychotherapy, theatre, and drama therapy (1990).

With the parallels of EI and theatre in mind, some business schools in the U.S.

have started offering acting electives. These courses vary in length from one-week to

semester-long. They tend to focus on improving students’ communication and

presentation skills. Carnegie Mellon began offering a theater class tailored to MBAs

almost 25 years ago (Damast, 2007). These drama electives don’t train students to be

actors. Rather, they use “strategies from the stage to enhance students’ approach across a

range of business situations” (Steen, 2013). The effects of these classes have not yet been

studied extensively.

Rather than focus on theater classes for MBAs, I will take a broader scope. This

paper will seek to answer the question: “Does participation in an acting course increase

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one’s emotional intelligence? Along which dimensions?” using a mathematical approach.

By examining introductory instruction, I seek to quantify (some of) the value of arts

education. My hope is that by linking the theatre arts to emotional intelligence, which is,

in turn, linked to personal and professional success, parents, schools, businesses and

policymakers will use the results of this study to advocate for budgetary increases for

drama programs.

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4 Literature Review

Few studies have quantitatively investigated the impacts of arts education

programming. This is due, in part, to the lack of quantitative measures available to

effectively evaluate the arts. In contrast, STEM programs are consistently measured using

standardized tests. Standardized tests aren’t available for theatre, and it’s unlikely that

one could be developed. Despite this fact, existing literature shows that theatre could

have an impact on emotional development. Studies have found evidence of tangible

benefits from the theatre, both from a patronage standpoint and a participatory one.

A recent study by Jay P. Greene at the University of Arkansas found that high

school students who viewed live performances of Hamlet and A Christmas Carol were

more adept at reading other people’s emotions than those who only read the plays or saw

film adaptations. According to Greene, “the intensity and immediacy of live performance

appears to convey the ability to recognize what other people are thinking and feeling in a

way that a movie or text could not” (2015, p. 9). Additional analysis by the research team

found that past theater experience is also significantly and positively related to the ability

to read the emotions of others. If being an audience member is beneficial, there should

also be favorable effects for those involved in the production.

A qualitative study out of the University of Illinois tracked the emotional

development of adolescents during a high school production of Les Miserables. In the

study, authors Reed W. Larson and Jane R. Brown interviewed students, parents and

faculty throughout the rehearsal process, as well as two years later. They determined that

the youth theatre program appeared to “provide a particularly rich microcosm for

emotional experiences and development” (2007, p. 1084). The youth in the program

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described gaining understanding of the relationships between immediate emotions and

individuals’ differing personalities. Larson and Brown attribute this gain to both the

drama production itself, as well as its emotional culture. Thus, whatever inherent benefits

come from the practice of theatre can be exacerbated with a healthy and open emotional

culture.

Some innovative teaching artists are already trying to find ways to promote

emotional intelligence learning in the drama classroom. A professor at Arizona State

University has developed a module called Emotional Intelligence Instruction through

Drama, but I have found no data on its supposed effectiveness. Nor have I found any

accounts of its implementation. In the U.K., a teaching artist is placing boys into physical

theatre classes as a means of closing the gender achievement gap. And while that teacher

draws upon the concepts of emotional intelligence to drive his argument, he doesn’t cite

any studies that suggest that connection.

One study, from Reinders Research, attempts to show a direct relationship

between theatre education and EI development. This paper, First Stage Children’s

Theatre Emotional Intelligence Evaluation, follows a sample of elementary school

students placed into a theatre arts and literacy program in Milwaukee, Wisconsin. The

program was five and a half months in duration. Researchers administered an emotional

intelligence test (the Six Seconds’ SEI-YV survey test) at the beginning and again at the

end of the program. Using this methodology, they found that one third of students saw a

positive change in EI. Those who did improve, made notable gains in all eight categories

that the test measured. However, the study did not have a control group, and post-

program data was only collected for about 60% of students. The evaluation did not

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account for any other factors that might have contributed to the emotional development

of the students. So, the exploratory evaluation’s conclusions are somewhat murky.

To make a more convincing argument for the connection between EI and theatre,

I decided to modify this study in two key ways:

(1) Using the framework provided by Reinders, I devised a controlled

experiment. For the results of the experiment to be conclusive, the

experiment had to control for confounding variables, like time.

(2) I also chose to focus on adults. Most of the limited empirical research I

have found is focused explicitly on children and adolescents. But, to

draw generalizable conclusions that could be applied to school

programs, as well as dramatic corporate training programs, I sought to

examine subjects whose brains were fully developed.

Beyond those crucial changes, my experiment also uses a different measurement

of emotional intelligence, and the granular nature of my analysis approach stands up to

more scrutiny. In general, alterations to the framework were instilled to give the study’s

conclusions more credibility.

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5 Methodology

5.1 Experimental Design

With the help of my advisor, I devised a two-pronged experiment for testing the

effects of acting classes on emotional intelligence. Both prongs of the experiment

followed the same format. Initially, subjects were tested for emotional intelligence. Then,

subjects took an acting course. After the acting course, a final test for emotional

intelligence was administered. To run my experiment, I recruited students from across

Northwestern University. The students who participated fell into three distinct groups:

(1) THEATRE 143-0 Students

(2) Seminar Course Students

(3) Control Group Students.

THEATRE 143-0 Students

The first fork of the study utilized a theatre course already built into the

Northwestern University course catalog, THEATRE 143-0 (Acting for Non-Majors). A

copy of the syllabus for this class can be found in Appendix A. The course professor,

Shawn Douglass, allowed his enrolled students to participate in the research on a

voluntary basis.

In the winter quarter, 4 students were recruited. In the spring quarter, an

additional 12 students joined the study. Due to roadblocks in the approval process, the

winter quarter subjects were tested in week 3 of the course. They were retested 10 weeks

later. The spring quarter subjects were tested in weeks 1 and 7 of the course to allow time

for analysis of results.

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Because the students were invited to participate in the study after they had

enrolled in THEATRE 143-0, there is the potential for bias. Students who choose to

enroll in an acting elective might have a vested interest in theatre and may have previous

acting experience. So, while this group was convenient, we determined that a more

random sample would be beneficial to the study.

Seminar Course Students

The second fork of the study used a random sample of students. Students enrolled

in the School of Communication and those who had already taken a college-level acting

course were considered ineligible. The students were placed into an introductory acting

seminar course, taught by Professor Mary Poole. The course met once per week for two

hours, for a total of five weeks. It is important to note that the course was not tailored to

the emotional intelligence.

Because of the intense time commitment required, it was difficult to recruit

subjects for the study. Ultimately, 7 students were placed into the seminar course. To

maintain this N, subjects were allowed to miss one seminar.

Control Group Students

In order to control for confounding variables, a third group was tested. This

group, aptly called the “Control Group,” consisted of a random sample of Northwestern

students. These students were screened using the same criteria as those in the Seminar

Course group: the students could not be enrolled in the School of Communication, and

they could not have already taken a college-level acting course.

20 students were recruited in the spring to be part of the control group. The

control group tested in weeks 1 and 7, along with the spring THEATRE 143-0 subjects.

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The results of their tests were intended to serve both the Seminar Course group and the

THEATRE 143-0 group.

5.2 The Test

To approach this question from a mathematical standpoint, I needed to be able to

reliably quantify the emotional intelligences of research subjects. I identified the Mayer-

Salovey-Caruso Emotional Intelligence Test (MSCEIT) as the best inventory for my

study. There were three important differentiators that made the MSCEIT attractive to me.

First, the MSCEIT is broken up into multiple sections, each with their own sub-

score. The test provides one overall emotional intelligence score, but it also provides

scores for each of the four branches of the EI, as well as eight task scores. Details about

each of the MSCEIT’s scores can be found in Description of the Data. Because each

administration of the MSCEIT results in 15 different scores, the data can be cut in many

ways. This feature of the MSCEIT allows for granular analysis.

Second, the MSCEIT is an ability-based test. Many emotional intelligence tests

are self-report, meaning that test-takers are required to gauge their own emotional

intelligences. But someone with a low EI will lack self-awareness, and his or her self-

evaluation will carry little value. Furthermore, people are notoriously awful at evaluating

their own capabilities. The Dunning-Kruger effect would almost certainly cause issues in

self-reported data. The Dunning-Kruger effect describes a cognitive bias wherein people

fail to adequately assess their own levels of competence. Incompetent people tend to

believe they are more competent than they actually are – due to their incompetence.

Conversely, competent people tend to underestimate their abilities. Thus, self-

assessments are not ideal for measuring intelligences. However, the MSCEIT does not

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employ self-assessment in any of its sections, making it an appropriate inventory for my

study.

Third, administration of the MSCEIT is simple. The test is inexpensive and does

not require a psychologist. It is administered via computer, and takes 30-45 minutes for

subjects to complete. Though the MSCEIT does not have multiple forms, the test features

high test-retest reliability. These considerations made the MSCEIT the clear choice for

my research.

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6 Description of Data

The analysis presented in this paper is drawn from the results of my primary

research study. The dataset consists of 78 individual administrations of the Mayer-

Salovey-Caruso Emotional Intelligence Test (MSCEIT): 2 for each of the 39 subjects in

the study. 20 of these subjects acted as “controls,” and the other 19 were part of the

experimental group. To better understand the implications of the analysis, it is helpful to

keep in mind the MSCEIT’s structure. A visual overview of the test’s format can be

found in Figure 1.

6.1 Format of the MSCEIT

The MSCEIT is composed of individual items that are grouped into eight different

tasks: Faces, Pictures, Facilitation, Sensations, Blends, Changes, Emotional Management

and Emotional Relations. Within tasks, items are homogenous. Across tasks, items are

Figure 1: The structure of the Mayer-Salovey-Caruso Emotional Intelligence Test ImageSource:Revelian

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heterogeneous. Though the MSCEIT does report the results of the tasks to generate

scores, it is not recommended to analyze the results of each individual task.

Rather, higher-level EI scores should be used. Each of the four branches of the

MSCEIT is made up of two tasks. The four branches, as described by the test authors in

the MSCEIT User’s Manual, are:

(1) Perceiving Emotion (PEIQ)

PEIQ measures the subject’s ability to recognize how they and others

around them are feeling. The two elements of this branch are the Faces

and the Pictures tasks. In the Faces task, subjects are asked to identify how

a person feels by analyzing their facial expressions. In the Pictures task,

they gauge the extent to which landscapes and images express emotions.

(2) Facilitating Thought (FEIQ)

FEIQ measures the subject’s ability to generate emotion, and then reason

with this emotion. The two elements of this branch are the Facilitation and

Sensations tasks. In the Facilitation task, subjects are assessed by their

ability to generate a mood to support thinking and reasoning. In the

Sensations task, subjects compare different emotions to different situations

such as light, color, and temperature.

(3) Understanding Emotions (UEIQ)

UEIQ measures the subject’s ability to understand complex emotions and

how emotions transition from one stage to another. The two elements of

this branch are the Blends and Changes tasks. The Blends task requires

subjects to analyze blends of emotions for their parts and assemble simple

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emotions into compound emotions. The Changes task assesses subject’s

knowledge of emotional “chains,” how emotions transition from one to

another.

(4) Managing Emotions (MEIQ)

MEIQ measures the subject’s ability to manage and regulate emotions in

themselves and others. This includes skills like knowing how to calm

down after feeling angry or being able to empathize with and alleviate the

anxiety of another person. The two elements of this branch are the

Emotional Management and Emotional Relations tasks. The Emotional

Management task requires subjects to rate the effectiveness of alternative

actions in achieving a certain result in situations where a person must

regulate his or her own emotions. The Emotional Relations task asks

subjects to incorporate their own and others' emotions into decision-

making.

All of the branch scores are used to determine MSCEIT area scores. The

Perceiving Emotion and Facilitating Thought branch scores are used to determine the

Experimental Area score (EEIQ). The Understanding Emotions and Managing Emotions

branch scores are used to determine the Strategic Area (SEIQ) score. Both area scores are

then used to determine the overall Emotional Intelligence score (EIQ).

6.2 MSCEIT Score Reporting

The MSCEIT’s items have answers that are objectively more correct than others.

The correctness of responses, and thus the scoring of the test, can be determined in two

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ways: general consensus and expert consensus. Brackett and Salovey explain the

differences between these two scoring techniques:

“In consensus scoring, the MSCEIT items are given to a large, heterogeneous

sample of individuals. Responses are tallied from the normative sample, and respondents

are given «credit» for «correct» answers to the extent that their answers match those

provided by the normative sample (i.e., the general public). Response scores are weighted

by the proportion of the normative sample who also provided that answer. The

assumption is made that large samples of individuals converge on correct answers

(Legree, 1995).

Expert scoring relies on properly identified emotions experts to indicate what they

believe are the correct answers. Respondents receive credit for correct answers to the

extent that they match those of the experts. For example, if .71 of the expert or normative

samples says that there is a moderate amount of sadness in a face and a person chooses

that answer (i.e., also indicates that the particular stimulus includes a moderate amount of

sadness), that person’s score is incremented by .71” (pg. 36).

This study utilizes general consensus scoring, because this method has been

shown to be slightly more reliable than expert consensus scoring. A table of reliability

measures can be found in Figure 2 below.

Overall PEIQ FEIQ UEIQ MEIQ General Consensus 0.93 0.91 0.79 0.80 0.83 Expert Consensus 0.91 0.90 0.76 0.77 0.81

Figure 2: Reliability of MSCEIT, by scoring method

The MSCEIT’s 7 scores are reported as emotional intelligence quotients (EIQs).

These scores are reported like “traditional intelligence scales.” That is, scores are

reported so that the average score is 100 and the standard deviation is 15. Because of this,

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it is easy to convert MSCEIT scores to percentiles rankings. Mayer and Salovey provide

guidelines for interpreting MSCEIT scores, and they can be found in Figure 3.

EIQ Score Range Qualitative Range

<69 Consider Development

70-89 Consider Improvement

90-99 Low Average Score

100-109 High Average Score

110-119 Competent

120-129 Strength

130+ Significant Strength Figure 3: Guidelines for interpreting range of MSCEIT scores

6.3 Scored Dataset

The scored dataset includes individual item responses, scored item responses, as

well as task, branch, area and total Scores for the 84 administrations of the MSCEIT (42

study participants, tested twice). It also includes granular percentile rankings. The dataset

was scored using general consensus scoring, with no corrections for gender, ethnicity, nor

age.

Each row of data was categorized by the time the test was taken, as well as the

group to which the test taker belonged. Group 1 consists of the Class Group. Group 2

consists of the Seminar Group. Group 3 consists of both treatment groups.

One participant from the Seminar Group was unable to complete the second

assessment under the required conditions, so that participant’s responses were dropped

from the dataset before analysis.

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7 Results

7.1 Summary Statistics

Figure 4 shows the mean change in total emotional intelligence score for each

group. Also included in the figure are the 95% confidence intervals for these means.

Figure 5 shows each group’s pre-test and post-test scores. Upon initial observation, it

appears that the Control Group and the Seminar Group improved. However, the Class

group exhibited a decline in scores.

Figure 4: Mean change in total score, by group, with 95% confidence interval

Pre-test Post-test Difference Growth N

Control 98.1005 101.1375 3.0371 3.10% 21Class 100.4813 98.0897 -2.3916 -2.38% 15

Seminar 103.9215 110.2274 6.3059 6.07% 6Treatment 101.4642 101.5576 0.0934 0.09% 21

Figure 5: Mean pre-test and post-test scores, by group

-10

-5

0

5

10

15

20

Control(N=20)

Class(N=15)

Seminar(N=6)

Treatment(N=21)

Mean Change in Total EI Score, by Group

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7.2 Paired t-tests

To determine if the changes in performance were meaningful, I ran a series of

paired t-tests. Ultimately, I decided to run the test using unequal variances. Paired t-tests

assume normality, but because of the small sample size associated with this study, the

results might be considered invalid. However, the results were compared with the results

of the Mann-Whitney U-test, which does not require normality. The significance of the

results was consistent across both the t-tests and the U-tests. The results of the t-tests can

be found in Figure 6. The figure indicates the difference score between the treatment

group and the control group, for each branch (PEIQ, FEIQ, UEIQ and MEIQ) and area

score (EEIQ and SEIQ), as well as the total score.

Overall EEIQ SEIQ PEIQ FEIQ UEIQ MEIQ Class -5.4287*** -8.4439*** -0.9904 -5.5926*** -7.8667*** 3.3785** -4.2476***

Seminar 3.2688* 3.1097 0.2834 -0.0516 5.8221** -0.1396 0.5136Treatment -2.9437** -5.1429*** -0.6265 -4.0095** -3.9557** 2.3733** -2.8873**

Figure 6: Difference scores between treatment groups and control groups.

*** - 95% significance, ** - 85% significance, * - 75% significance

Fewoftheresultsweresignificantatthe95%level,butduetothe

exploratorynatureofthestudy,Ialsochosetomarkresultssignificantatthe75%

and85%levels.Contrarytotheoriginalhypothesisofthestudy,thereappearstobe

anegativeeffectassociatedwithemotionalintelligenceandstructuredtheatre

education.

TheClassgroupdeclinedineveryscoreandsub‐score,exceptforUEIQ.A

vastmajorityofthesedownturnsaresignificantatthe95%level.However,the

Seminargroupgenerallysawincreasedperformance.Thesegainsweresignificant

atthe75%leveloverall,andatthe85%levelforFEIQ.Becausethesamplesizeof

THEATREANDEMOTIONALINTELLIGENCE

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theSeminargroupwascomparativelylow,statisticalsignificancewasdifficultto

achieve.

ItshouldbenotedthattheTreatmentgroupisunfairlyweightedtowardsthe

Classgroup,whichexperienceddeclinesinMSCEITperformance.Thus,thesetwo

groupsshouldbediscussedseparately,andnotasonelargergroup.

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8 Discussion

Theresultsofthestudyarebothunexpectedandsomewhatcounterintuitive.

Basedonpreviousresearch,Ihopedtoobserveanincreaseinscoresinboth

treatmentgroups.However,theSeminargroupshowedimprovement,andtheClass

groupshowedsignificantdeclines.Itseemsunlikelythatanactingcoursewould

haveadecidedlynegativeeffectonemotionalintelligence.WhileIcannotrulethis

possibilityout,Iwillalsodiscussseveralsensiblejustificationsfortheobserved

results.

ThestudentsintheNorthwesternUniversityclassweremorelikelytohavea

fullcourseschedule.TheSeminargroupwasfullofstudentsintheirlastyearat

Northwestern,wholikelydidn’thavemanyothercommitments.Thus,these

studentswereabletosqueezeintheweekly2‐hourclass.However,studentsinthe

THEATRE143‐0courseprobablyhadfullclassschedulesandout‐of‐classroom

commitmentsthatcontributedtostresslevels.Withoutbeingabletocontrolfor

stress,Iamunabletodetermineifstresswasanexogenousvariablethatresultedin

scoredeclines.

Beyondstresslevels,therewereotherdifferencesbetweenthetwo

treatmentgroups.TheClassgroupwasexposedtoahighlystructuredenvironment

withassignmentsandrehearsalprocesses.Perhapsthefactthatstudentswere

beinggradedhadanadverseeffectontheirdevelopment.Incontrast,theSeminar

coursewasmorefreeform.Studentsweretaskedwithfollowingtheprofessor’s

instructionsandallowingthemselvestobefullypresentinthespace.These

THEATREANDEMOTIONALINTELLIGENCE

26

differentclassroomdynamics,aswellasthevariedteachingstylesoftheprofessors

mayhavehadeffectsonstudentperformance.

Theremayhavealsobeenissueswiththecontrolgroup.Eachtreatment

group’sperformancewascomparedtothatofthecontrolgroup.But,duetostudent

availability,moststudentsinthecontrolgroupwereseniors.Thesestudentslikely

hademptyschedules,andlackedsomeofthestressthattheothergroups

experienced.Additionally,manyofthemwereintheMMSSprogram.Thiswasagain

duetoavailability.Perhapsthesamplewastoouniformforafaircomparison.

Ialsoworkedwithaverysmallgroupofstudents.Becausethesamplesize

wassosmall,thereisalotofopportunityforrandomfluctuation.Thus,itwas

difficulttoachievestatisticalsignificanceatthegenerallyapprovedlevelsof95%.

Ideally,thetestscouldberunagaininamorecontrolledenvironmentwith

additionalsubjects.

Eventhoughtheresultsarenotstatisticallysignificant,it’sstillinterestingto

lookattheperformanceoftheSeminargroup.Asonemightexpect,thegroup

excelledindevelopingtheirExperimentalarea–whichincludestaskslikereading

facesandfacilitatingemotions.It’sinterestingtoseethattheStrategicareasawno

improvement.

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9 Conclusion

My exploratory research suggests that there is a possible link between theatre and

emotional intelligence. Previous studies have shown that theatre education, participation

and patronage can each have a positive effect on emotional understanding and

intelligence. However, the results of my experiment are less decisive. The Class group

worsened their emotional intelligence, while the Seminar group improved theirs. Thus,

the link between theatre and EI might be positive or negative, and requires further

controlled study. Additional studies might explore varying class durations and structures,

teaching styles, and control for participant’s stress levels.

.

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10 Appendix A: THEATRE 143-0 Syllabus

ACTING: BASIC TECHNIQUES THEATRE 143-0-21 WINTER Quarter, 2015 South Studio Monday/Wednesday 9:30-10:50am Shawn Douglass Email: s-douglass@northwestern.edu Phone: 312.343.1982 Office Hours: M, W 11:00-12:00pm, please make appointment by email or text Office: Theatre and Interpretation Center, Room 208 What does it mean to act? What does it mean to “be in the moment”? What does it mean to want? How do you go about getting what you want? How does environment affect behavior? What does your life experience have to do with a character in a play (or vice versa)? In this course you will learn how: To INCREASE ATTENTION to human behavior and the world around you To LISTEN and RESPOND spontaneously To recognize how CIRCUMSTANCES influence your actions To identify GOALS that will form the basis for clear ACTION To apply the above skills in the creation of CHARACTER Using exercises, outside assignments, observation of life, and improvisation you will be introduced to basic principles of acting. You will learn the fundamentals of creating character and a simple method to turn the written word into action. Finally, you will apply these principles toward scene work using simple “content-less” scenes and a scene from a play. Although there are written components to the course, the essence of the class is in the DOING. You must come ready to risk, to play, to work, and to question. You must also spend significant time outside of the class working with scene partners. REQUIRED TEXTS Play Script - TBA Readings provided by the Instructor

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REQUIREMENTS (1000 points possible) 1. Enthusiastic Participation. Enthusiastic participation means throwing yourself boldly

into exercises, being prepared to discuss assignments or present scenes, working cooperatively with your partner or group, and completing all assignments on time and in a thoughtful manner. All written assignments must be typed. (200 points)

2. Assignments. In addition to the following assignments, you should be prepared to

discuss in class any readings that are assigned. (250 points total) Most Amazing Thing 20 pts Me’s 50 pts Listening 20 pts One Minute Activity 50 pts 1-20 Action Scenes 50 pts Objectives in a Day list 10 pts Lady of Larkspur Lotion 50 pts 3. Rehearsal and presentation of a 1-2 minute monologue chosen by student. The

monologue will be rehearsed and performed with a partner, then again as an audition piece to an imaginary auditor. (100 pts)

4. Rehearsal and presentation of a short “content-less” scene with 2 sets of imaginary

circumstances, employing the techniques you have learned. Out of classroom rehearsal time required. (150 pts)

5. Rehearsal and performance of a memorized scene from a play chosen by

instructor. Out of classroom rehearsal time required. Scenes will be presented twice. The first presentation should be fully memorized and “blocked” and will be followed by notes and work with the instructor. You will keep a journal about the rehearsal process. The second and FINAL presentation will demonstrate work done based on those notes. FINAL is scheduled for our last day of class – Wednesday, March 11 (9:00-10:50am) (200 pts)

6. Attend 2 plays. The plays may be professional, university, or student-produced

productions. Operas, musicals, revues, improv shows, and movies do not count. Write a two page typewritten response to the work of an actor or actors in the production. The first paper is due no later than Monday, February 2. The second paper is due no later than Monday, March 9. Late papers will not be accepted. You must attach a ticket stub or program from the production to each paper. You will receive a handout with more guidance on format and content. (100 pts, or 50 pts each)

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GRADES You will not be graded on your talent. The criteria for evaluating your work in this course will include your seriousness of purpose, the effort you put forth, the detail with which you work, and the progress you make. Grading Scale A 930-1000 pts A- 900-929 B+ 870-899 B 830-869 B- 800-829 C+ 770-799 C 730-769 C- 700-729 D+ 670-699 D 630-669 D- 600-629 F 0-599 ATTENDANCE Strictly enforced. You will be allowed only two absences, with the exception of religious holidays (please tell me in advance). For each subsequent absence, your grade will be reduced a half letter grade. Excessive tardiness may also affect your grade. If you are tardy, it is your responsibility to check that the instructor has marked you in attendance. There will be no “make ups” scheduled for scene presentations. If there is an extraordinary circumstance that prevents you from attending a number of classes (mononucleosis, surgery, death in the family, etc.), it is your responsibility to notify me as soon as possible so we can decide how to address it. ATTIRE Comfortable, loose-fitting clothes that allow ease of movement should be worn to class. Bring a pair of sweats to change into before class if necessary. Shoes should also be practical – no flip-flops or heels!

o

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11 Appendix B: Stata Output

11.1 Total Scores

. ttest diffss_tot, by(group1) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.037084 1.679773 7.697688 -.4668613 6.54103 1 | 15 -2.391602 1.370972 5.309751 -5.332044 .5488406 ---------+-------------------------------------------------------------------- combined | 36 .7751319 1.207669 7.246013 -1.676566 3.22683 ---------+-------------------------------------------------------------------- diff | 5.428686 2.168226 1.022226 9.835146 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 2.5037 Ho: diff = 0 Satterthwaite's degrees of freedom = 33.9799 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9914 Pr(|T| > |t|) = 0.0173 Pr(T > t) = 0.0086 . ttest diffss_tot, by(group2) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.037084 1.679773 7.697688 -.4668613 6.54103 1 | 6 6.305921 3.678375 9.010143 -3.149644 15.76149 ---------+-------------------------------------------------------------------- combined | 27 3.763492 1.528861 7.944195 .6208736 6.906111 ---------+-------------------------------------------------------------------- diff | -3.268837 4.043771 -12.77098 6.233307 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -0.8084 Ho: diff = 0 Satterthwaite's degrees of freedom = 7.2243 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.2223 Pr(|T| > |t|) = 0.4447 Pr(T > t) = 0.7777 . ttest diffss_tot, by(group3) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.037084 1.679773 7.697688 -.4668613 6.54103 1 | 21 .0934049 1.636505 7.499409 -3.320285 3.507095 ---------+-------------------------------------------------------------------- combined | 42 1.565245 1.180783 7.652348 -.819395 3.949884 ---------+-------------------------------------------------------------------- diff | 2.943679 2.345163 -1.796171 7.68353 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 1.2552 Ho: diff = 0 Satterthwaite's degrees of freedom = 39.9728 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.8917 Pr(|T| > |t|) = 0.2167 Pr(T > t) = 0.1083

11.2 Area Scores

. ttest diffss_exp, by(group1) unequal Two-sample t test with unequal variances

THEATREANDEMOTIONALINTELLIGENCE

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------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.96143 1.871577 8.576645 .0573881 7.865472 1 | 15 -4.482468 2.032836 7.873141 -8.842468 -.1224682 ---------+-------------------------------------------------------------------- combined | 36 .4431391 1.533451 9.200707 -2.669932 3.55621 ---------+-------------------------------------------------------------------- diff | 8.443898 2.763191 2.81407 14.07373 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 3.0559 Ho: diff = 0 Satterthwaite's degrees of freedom = 31.7994 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9977 Pr(|T| > |t|) = 0.0045 Pr(T > t) = 0.0023 . ttest diffss_exp, by(group2) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.96143 1.871577 8.576645 .0573881 7.865472 1 | 6 7.071097 5.664152 13.87428 -7.48907 21.63126 ---------+-------------------------------------------------------------------- combined | 27 4.652467 1.879103 9.764106 .7899153 8.515019 ---------+-------------------------------------------------------------------- diff | -3.109667 5.965352 -17.6299 11.41056 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -0.5213 Ho: diff = 0 Satterthwaite's degrees of freedom = 6.13313 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.3102 Pr(|T| > |t|) = 0.6204 Pr(T > t) = 0.6898 . ttest diffss_exp, by(group3) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.96143 1.871577 8.576645 .0573881 7.865472 1 | 21 -1.18145 2.391635 10.95985 -6.170313 3.807414 ---------+-------------------------------------------------------------------- combined | 42 1.38999 1.552649 10.06232 -1.745648 4.525629 ---------+-------------------------------------------------------------------- diff | 5.142879 3.036893 -1.005979 11.29174 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 1.6935 Ho: diff = 0 Satterthwaite's degrees of freedom = 37.8147 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9507 Pr(|T| > |t|) = 0.0986 Pr(T > t) = 0.0493 . . ttest diffss_rea, by(group1) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 1.345946 1.406468 6.445248 -1.587896 4.279788 1 | 15 .3554988 1.295455 5.017275 -2.422975 3.133973 ---------+-------------------------------------------------------------------- combined | 36 .9332595 .9725726 5.835435 -1.041168 2.907687 ---------+-------------------------------------------------------------------- diff | .9904471 1.91216 -2.896848 4.877742 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 0.5180

THEATREANDEMOTIONALINTELLIGENCE

33

Ho: diff = 0 Satterthwaite's degrees of freedom = 33.6899 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.6961 Pr(|T| > |t|) = 0.6079 Pr(T > t) = 0.3039 . ttest diffss_rea, by(group2) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 1.345946 1.406468 6.445248 -1.587896 4.279788 1 | 6 1.629316 1.744679 4.273574 -2.855526 6.114157 ---------+-------------------------------------------------------------------- combined | 27 1.408917 1.146353 5.956626 -.9474461 3.76528 ---------+-------------------------------------------------------------------- diff | -.2833699 2.240995 -5.152451 4.585711 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -0.1264 Ho: diff = 0 Satterthwaite's degrees of freedom = 12.3106 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.4507 Pr(|T| > |t|) = 0.9014 Pr(T > t) = 0.5493 . ttest diffss_rea, by(group3) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 1.345946 1.406468 6.445248 -1.587896 4.279788 1 | 21 .7194465 1.035896 4.747072 -1.441395 2.880288 ---------+-------------------------------------------------------------------- combined | 42 1.032696 .8640583 5.599738 -.712305 2.777697 ---------+-------------------------------------------------------------------- diff | .6264994 1.746778 -2.913573 4.166572 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 0.3587 Ho: diff = 0 Satterthwaite's degrees of freedom = 36.7652 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.6390 Pr(|T| > |t|) = 0.7219 Pr(T > t) = 0.3610

11.3 Branch Scores

. ttest diffss_b1, by(group1) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.584025 2.03831 9.34071 -.667815 7.835865 1 | 15 -2.008612 2.209796 8.558503 -6.748153 2.730929 ---------+-------------------------------------------------------------------- combined | 36 1.25376 1.554341 9.326043 -1.901719 4.409239 ---------+-------------------------------------------------------------------- diff | 5.592637 3.006311 -.5323093 11.71758 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 1.8603 Ho: diff = 0 Satterthwaite's degrees of freedom = 31.8289 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9639 Pr(|T| > |t|) = 0.0721 Pr(T > t) = 0.0361 . ttest diffss_b1, by(group2) unequal

THEATREANDEMOTIONALINTELLIGENCE

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Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.584025 2.03831 9.34071 -.667815 7.835865 1 | 6 3.532454 8.364681 20.4892 -17.96964 25.03455 ---------+-------------------------------------------------------------------- combined | 27 3.572565 2.340047 12.15924 -1.237471 8.382601 ---------+-------------------------------------------------------------------- diff | .0515709 8.609448 -21.37866 21.4818 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 0.0060 Ho: diff = 0 Satterthwaite's degrees of freedom = 5.60649 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.5023 Pr(|T| > |t|) = 0.9954 Pr(T > t) = 0.4977 . ttest diffss_b1, by(group3) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 3.584025 2.03831 9.34071 -.667815 7.835865 1 | 21 -.4254503 2.78435 12.7595 -6.233503 5.382602 ---------+-------------------------------------------------------------------- combined | 42 1.579287 1.732699 11.22917 -1.91997 5.078544 ---------+-------------------------------------------------------------------- diff | 4.009475 3.450698 -2.984533 11.00348 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 1.1619 Ho: diff = 0 Satterthwaite's degrees of freedom = 36.6535 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.8736 Pr(|T| > |t|) = 0.2528 Pr(T > t) = 0.1264 . . ttest diffss_b2, by(group1) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 2.484577 2.035129 9.326134 -1.760628 6.729783 1 | 15 -5.38216 2.024863 7.84226 -9.725059 -1.039262 ---------+-------------------------------------------------------------------- combined | 36 -.7932301 1.579142 9.474852 -3.999059 2.412599 ---------+-------------------------------------------------------------------- diff | 7.866738 2.870857 2.02593 13.70755 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 2.7402 Ho: diff = 0 Satterthwaite's degrees of freedom = 32.9992 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9951 Pr(|T| > |t|) = 0.0098 Pr(T > t) = 0.0049 . ttest diffss_b2, by(group2) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 2.484577 2.035129 9.326134 -1.760628 6.729783 1 | 6 8.306634 4.04462 9.907255 -2.090392 18.70366 ---------+-------------------------------------------------------------------- combined | 27 3.778368 1.84456 9.584617 -.0131805 7.569916 ---------+-------------------------------------------------------------------- diff | -5.822057 4.52777 -16.32732 4.683204 ------------------------------------------------------------------------------

THEATREANDEMOTIONALINTELLIGENCE

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diff = mean(0) - mean(1) t = -1.2859 Ho: diff = 0 Satterthwaite's degrees of freedom = 7.72845 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.1178 Pr(|T| > |t|) = 0.2357 Pr(T > t) = 0.8822 . ttest diffss_b2, by(group3) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 2.484577 2.035129 9.326134 -1.760628 6.729783 1 | 21 -1.471076 2.265084 10.37992 -6.195958 3.253805 ---------+-------------------------------------------------------------------- combined | 42 .5067506 1.535239 9.949488 -2.593728 3.607229 ---------+-------------------------------------------------------------------- diff | 3.955654 3.045054 -2.200812 10.11212 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 1.2990 Ho: diff = 0 Satterthwaite's degrees of freedom = 39.5502 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.8993 Pr(|T| > |t|) = 0.2015 Pr(T > t) = 0.1007 . ttest diffss_b3, by(group1) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 -1.419304 1.139614 5.222365 -3.796496 .9578886 1 | 15 1.959219 1.624967 6.29347 -1.525989 5.444427 ---------+-------------------------------------------------------------------- combined | 36 -.0115859 .9758378 5.855027 -1.992642 1.96947 ---------+-------------------------------------------------------------------- diff | -3.378522 1.984751 -7.453427 .6963823 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -1.7022 Ho: diff = 0 Satterthwaite's degrees of freedom = 26.6462 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.0502 Pr(|T| > |t|) = 0.1004 Pr(T > t) = 0.9498 . ttest diffss_b3, by(group2) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 -1.419304 1.139614 5.222365 -3.796496 .9578886 1 | 6 -1.558907 1.710808 4.190607 -5.956679 2.838866 ---------+-------------------------------------------------------------------- combined | 27 -1.450326 .9498529 4.935581 -3.402777 .5021242 ---------+-------------------------------------------------------------------- diff | .139603 2.055622 -4.444815 4.724021 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 0.0679 Ho: diff = 0 Satterthwaite's degrees of freedom = 9.93277 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.5264 Pr(|T| > |t|) = 0.9472 Pr(T > t) = 0.4736 . ttest diffss_b3, by(group3) unequal

THEATREANDEMOTIONALINTELLIGENCE

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Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 -1.419304 1.139614 5.222365 -3.796496 .9578886 1 | 21 .9540402 1.286708 5.896439 -1.729987 3.638067 ---------+-------------------------------------------------------------------- combined | 42 -.2326317 .8688592 5.630851 -1.987328 1.522065 ---------+-------------------------------------------------------------------- diff | -2.373344 1.718819 -5.848786 1.102098 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -1.3808 Ho: diff = 0 Satterthwaite's degrees of freedom = 39.4246 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.0876 Pr(|T| > |t|) = 0.1751 Pr(T > t) = 0.9124 . ttest diffss_b4, by(group1) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 2.946622 1.553356 7.118372 -.293622 6.186866 1 | 15 -1.300994 1.434112 5.55429 -4.376857 1.774869 ---------+-------------------------------------------------------------------- combined | 36 1.176782 1.127997 6.767983 -1.113174 3.466738 ---------+-------------------------------------------------------------------- diff | 4.247616 2.114141 -.050365 8.545597 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 2.0091 Ho: diff = 0 Satterthwaite's degrees of freedom = 33.6745 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9737 Pr(|T| > |t|) = 0.0526 Pr(T > t) = 0.0263 . ttest diffss_b4, by(group2) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 2.946622 1.553356 7.118372 -.293622 6.186866 1 | 6 3.460205 2.356761 5.772862 -2.598042 9.518453 ---------+-------------------------------------------------------------------- combined | 27 3.060752 1.297206 6.740478 .3943075 5.727196 ---------+-------------------------------------------------------------------- diff | -.5135829 2.82263 -6.818073 5.790907 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -0.1820 Ho: diff = 0 Satterthwaite's degrees of freedom = 9.8243 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.4297 Pr(|T| > |t|) = 0.8593 Pr(T > t) = 0.5703 . ttest diffss_b4, by(group3) unequal Two-sample t test with unequal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- 0 | 21 2.946622 1.553356 7.118372 -.293622 6.186866 1 | 21 .0593487 1.287009 5.897816 -2.625305 2.744002 ---------+-------------------------------------------------------------------- combined | 42 1.502985 1.021443 6.619706 -.5598601 3.565831 ---------+--------------------------------------------------------------------

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diff | 2.887274 2.017252 -1.19414 6.968687 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = 1.4313 Ho: diff = 0 Satterthwaite's degrees of freedom = 38.6637 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.9198 Pr(|T| > |t|) = 0.1604 Pr(T > t) = 0.0802 . endofdo‐file

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