Quantitative Data Analysis

(Using SPSS)

Albard Khan, M.Ed

Saturday, 7 November 2015

Quantitative versus qualitative research

1. Quantitative research is “explaining phenomena

by collecting numerical data that are analysed

using mathematically-based methods (in

particular: statistics)” (Allaga & Gunderson, 2002).

2. Qualitative research relies heavily on “the views of

participants…collects data consisting largely of

words (or text) from participants, and analyse

these words for themes” (Creswell, 2008, p. 46).

Quantitative versus qualitative(cont.)

1. Quantitative research is concerned with numerical

data, or numbers.

2. Qualitative research is interested with words or texts.

3. SPSS is exclusively a quantitative data analysis tool.

4. What about qualitative research such as interviews,

case studies, ethnographic research, and discourse

analysis; what software is to be used?

5. For qualitative research, use other softwares such as

nVivo.

Pair Discussion

With the person next to you, discuss if the

following research is quantitative, qualitative, or

mixed?

The following excerpts were taken from

educational research reports. They are either

taken from the abstract or the full report of the

research.

1

“A set of policy documents was collected and

analysed against literature on international

schools and education decentralization.”

Kustulasari, 2009, The international school standard project in

Indonesia: A document analysis

2

“In this paper, we use data from Indonesia to

examine the effectiveness of public versus

private schools. We use labour market earnings

as our measure of effectiveness.”

Beare, 2000, The effectiveness of private versus public schools: The

case of Indonesia

3

“A survey questionnaire was designed to elicit

perceptions about the impact of prior learning,

competence in language and communication,

quality of student-staff relations and cultural

interactions on student learning.”

Ramburuth & Tani (2009), The impact of culture on learning: exploring student

perceptions. Multicultural Education & Technology Journal, Vol. 3 Iss: 3, pp.182 - 195

4

“Data were collected during one academic

semester through in-depth interviews, a focus

group interview, classroom observations, and

collection of relevant documents.”

Tatar, 2005, Classroom participation by international students

5

“In stage 1, 1209 questionnaire responses were

received from Y1 and Y2 students across these

institutions in the identified subjects. In stage 2

we interviewed the students at key decision

making moments.”

Reay, 2008, The socio-cultural and learning experiences of working

class students in higher education

6

“The project interviewed 162 first-year students

at the University of the Arts, London, a university

with a high proportion of international students. ”

Sovic, 2009, Hi-bye friends and the herd instinct: international and

home students

7

“A representative sample of undergraduate and

postgraduate international students at a large

Australian university (n = 979, 64% females)

completed a mail-back survey examining their

perceptions of social connectedness.”

Rosenthal, 2009, Social connectedness among international students

What QUANT research can answer:

1. When we want quantitative answer, e.g. how many

Tarbiyah students came from SMA? How many from

MA?

2. When we want to study numerical change, e.g. is

academic achievement going up or down this year?

3. When we want to explain phenomena with many

factors, e.g. what factors predict students’ English

performance?

4. When we want to test hypotheses, e.g. is that true that

a romantic person tends to have higher GPA?

What QUANT research CANNOT answer:

1. When we want to explore a problem in-depth.

2. When we want to develop theories and hypotheses.

We have to study the literature or conduct qualitative

study.

3. If the issues are particularly complex.

4. When we want to reveal the meaning of particular

events and circumstances.

Do you agree or do you not agree?

“What you cannot measure doesn’t exist.”

(Anonymous)

Research Design: Experimental,

Quasi-experimental and Non-

experimental

Experimental Design

Definition

“A test under controlled conditions that is made to demonstrate a known truth or

examine the validity of a hypothesis.” (Muijs, 2004, p. 13).

Experiment group vs control group

As in natural science experiments, control groups receive no treatment while

experiment groups do.

Purpose

To establish causality between variables.

Usually involves pre-tests – experiment – post-tests.

Quasi-experimental Design

Definition

This is almost the same as the experimental design in that extraneous factors are

controlled, but it differs from the experimental design as allocation of group is not

randomized.

Experiment group vs comparison group

As in natural science experiments, comparison groups receive no treatment while

experiment groups do.

Purpose

To establish causality between variables.

Usually involves pre-tests – experiment – post-tests.

Non-experimental Design

1. Survey research

2. Observational research

3. Dataset analysis

Today, our focus is on survey research, as it is the most popular and

easiest method to conduct compared to experimental and quasi-

experimental design.

In non-experimental design, we’re interested in relationship or

correlations among variables, not causality.

The online questionnaire

Let’s open the questionnaire

1. How many sections are there?

Three sections:

Demographic information (Name, GPA, Gender)

Romantic Beliefs Scale

Theories of Intelligence Scale

2. Romantic Beliefs Scale is unidimensional (measuring only one

domain/construct: romanticism).

3. Theories of Intelligence Scale is also unidimensional, measuring

whether someone has incremental or entity theory of intelligence.

Research Questions

Discuss in small groups

By looking at the questionnaire, figure out what questions

can be answered using the questionnaire/instrument!

Descriptive and Inferential Statistics

A. DESCRIPTIVE STATISTICS

1. How many respondents are male and female?

2. What is the mean of participants’ GPAs?

3. Is there a difference between male and female GPAs?

4. In general, how romantic are the respondents?

5. In particular, is there a difference between male and female

romantic belief levels?

6. In general, what is the type of respondents’ theories of

intelligence?

7. In particular, is there a difference between male and female

theories of intelligence?

Descriptive and Inferential Statistics (cont.)

B. INFERRENTIAL STATISTICS

1. Is the difference between male and female GPAs significant?

2. Is the difference between male and female romantic belief levels

significant?

3. Is there a correlation between romantic beliefs and GPA? If there

is, how strong, in what direction and how significant?

4. Is there correlation between romantic beliefs and intelligence

beliefs? If there is, how strong, in what direction and how

significant?

5. Is there a correlation between intelligence beliefs and GPAs? If

there is, how strong, in what direction and how significant?

Coding and Recoding

1. Only numbers can be analysed. You have to assign numbersto the data.

2. That’s why, we need to create a codebook.

3. MS Excel is the first place to go before SPSS.

4. In Theories of Intelligence Beliefs Scale, one half are quitethe opposite the other half. (We’ll do recoding on SPSS).

5. Types of Data: Nominal, Ordinal, Scale (separate slide,maybe later).

6. Let’s start creating a codebook.

7. Now let’s copy the data into SPSS.

Research questions answered

Let’s answer these questions (1)

A. DESCRIPTIVE STATISTICS

1. How many respondents are male and female?

2. What is the mean of participants’ GPAs?

3. Is there a difference between male and female GPAs?

4. In general, how romantic are the respondents?

5. In particular, is there a difference between male and female

romantic belief levels?

6. In general, what is the type of respondents’ theories of

intelligence?

7. In particular, is there a difference between male and female

theories of intelligence?

Let’s answer these questions (2)

B. INFERRENTIAL STATISTICS

1. Is the difference between male and female GPAs significant?

2. Is the difference between male and female romantic belief levels

significant?

3. Is there a correlation between romantic beliefs and GPA? If there

is, how strong, in what direction and how significant?

4. Is there correlation between romantic beliefs and intelligence

beliefs? If there is, how strong, in what direction and how

significant?

5. Is there a correlation between intelligence beliefs and GPAs? If

there is, how strong, in what direction and how significant?

Further topics for your personal studies...

Parametric and non-parametric tests

Factor analysis

Reliability analysis

Thank You