p091112001.pdf

USING EXCEL IN AN INTRODUCTORY

STATISTICS COURSE: A COMPARISON OF INSTRUCTOR AND STUDENT

PERSPECTIVES

Cynthia L. Knott

Marymount University, 2807 N. Glebe Road, Arlington, VA 22207

[email protected]

703-284-5727

G. Steube

Marymount University, 2807 N. Glebe Road, Arlington, VA 22207

[email protected]

703-284-5943

Northeast Decision Science Institute

March 2010

mailto:[email protected]

mailto:[email protected]

Using Excel in an Introductory Statistics Course of 13

Abstract

Almost all undergraduate business degree programs require that students take at least one

course in statistics. The instructor for these classes has a number of options in terms of selecting

the software package that will be used. Three popular options are R, PASW (formerly SPSS),

and Excel. This paper examines the advantages and disadvantages of these software choices in

order to assist the instructor with making an informed choice. The strengths and weaknesses of

these choices are explored in terms of both the instructor’s and student’s perspective. After

reviewing these assessments, the paper concludes that Excel is the best choice because of its low

cost, wide availability, familiar interface, and computational and charting flexibility.


Although most business schools require at least one course in statistics advances in

technology and the availability of statistical software has dramatically changed the way in which

these classes are taught. In the past, instructors presented statistics the old fashioned way, with

the “paper and pencil”. The students were expected to be involved in the mathematics as well as

the calculations. Students learned how to use the z-tables and calculate the statistics by hand.

Because of advances in technology, the reduction of cost in acquiring technology, and the

ubiquitous presence of technology, the way in which statistics courses can be presented has

changed to offer the instructor a wider range of choices. These choices center on the software

package that will be used in the class to perform calculations and present the findings in graphs

and charts. This paper focuses on some of the choices that instructors may face in selecting the

best software support for their introductory statistics class.

In the business school, statistics courses are applied rather than theoretical. It is

important that these learners understand the underlying calculations and theories, but more

significantly, these students must be able to apply, analyze, and interpret the results to improve

decision making in the business environment. Communication is the top skill sought by most

employers today (Barnes, 2009). Statistics courses should help the student in learning how to

communicate the results of their analysis in their future business environment. Therefore the

business statistics courses emphasize the communication of the results obtained from conducting

a wide range of hypothesis testing and other types of analysis. The use of statistical software

relieves the student and instructor from spending too much time on calculations and thus affords

more time to emphasize the understanding, interpreting, and communicating the results of these

computations.


This paper compares three popular statistical packages; R, PASW (formerly known as

SPSS) and Excel. Information about the R package can be obtained from the R Package for

Statistical Computing (Department of Mathematics and Statistics at Vienna University, n.d.);

PASW and Excel information can be located on the PASW website (SPSS Inc., 2009) and the

Microsoft website (Microsoft Inc., 2009b). The use of any of these three packages has a number

of strengths and deficiencies. These advantages and disadvantages are discussed from the

instructor and student point of view in this report. The discussion will provide input by which

assist an instructor in deciding among the three packages for his or her class in introductory

statistics.

Advantages and Disadvantages of R

The advantages and disadvantages from the instructor and student views for R are

summarized in Table 1 (instructor) and Table 2 (student), respectively.

Table 1

Advantages and disadvantages of R from the instructor view

Advantages

1. Availability Freely widely available at no cost (Zieffler & Long,

n.d.)

2. Flexibility and

customization

Because R is a programming language almost any result

can be achieved (Zieffler & Long, n.d.)

3.Up to date methods and

packages

Because R methods are written by users, R is more

current than many commercial statistical packages that

require updates to their base system (Zieffler & Long,

n.d.)

4. Broad coverage R packages are extensive and include a wide variety of

quantitative applications

5. Availability of help Because R has a large user network, help is readily

available on almost any topic


Disadvantages

1. Large data sets R may not handle large data sets as efficiently as SAS

(Zieffler & Long, n.d.)

2. Speed Some procedures in R could take days to run (Zieffler

& Long, n.d.)

3. Learning curve Because R is command line driven rather than a point

and click application, the learning curve is more

challenging than most commercial packages which use

a graphical interface

4. Lack of a spreadsheet view

of data

Unlike Excel and SPSS, R does not include a

spreadsheet view of the data set

5. Unfamiliarity R is less well-known than SPSS or Excel and may be

viewed less positively because of the lack of familiarity

Table 2

Advantages and disadvantages of R from the student view

Advantages

1. Availability No cost to the students and can be installed on their

computer and thus eliminate trips the University's

computer lab to do homework

2. Flexibility and

customization

After some investment in learning, R the student could

find available packages and develop their own tailored

applications

3.Up to date methods and

packages

As other users add packages to R to keep it current,

students can continue using R throughout their

academic and professional careers without concern

about updating their base packages to obtain the newer

software

4. Broad coverage Because of R broad coverage, students might be able to

use R in other quantitative courses

5. Availability of help Students can use the network of available user without

charge or other registration requirements to obtain

guidance on almost any aspect of R


Disadvantages

1. Large data sets May not be an issue for a student's academic use of R

because the data sets are relatively small

2. Speed The basic procedures used in an introductory statistics

course would not take days to run

3. Learning curve Students would need to invest time in learning R and

that investment may be challenging and time intensive;

the lack of graphic interface with point and click

capability would be a challenge for students who have

only worked with operating systems and applications

that furnish these abilities

4. Lack of a spreadsheet view

of data

The lack of spreadsheet view may be a concern to

students because they are tuned to table presentation of

data especially for business students

5. Unfamiliarity Students may not be any more unfamiliar with R than

SPSS; most students would be familiar with Excel

Advantages and Disadvantages of PASW

The strengths and weaknesses from the instructor and student views for PASW are

summarized in Table 3 (instructor) and Table 4 (student), respectively.

Table 3

Advantages and disadvantages of PASW from the instructor view

Advantages

1. Well known and supported PASW has been in the marketplace for many years and

many textbooks for introductory statistics courses are

based on this application. Other programs can easily

import SPSS data files (Harrington, McLeod, &

M.Clark, 2009).

2. Ease of use Because of its graphical user interface, a large of

number of statistical functions are easy to use and

access

3.Up to date PASW is generally updated at least once a year with

minor updates available on the corporate website


4. Broad coverage PASW includes a large number of statistical routines

appropriate for an introductory statistics course

5. Availability of help There are number of Excellent books that provide

comprehensive information on using PAWS; the

availability of the list serve for this package also

provides another source of guidance for specific issues

Disadvantages

1. Cost PASW is a commercial software that is available at a

relatively high cost [ JourneyEd (2009) list PASW

Graduate Pack for Windows at $199.98] ; some

applications are available only as another product with a

separate fee

2. Licensing complexity The license to use PASW is time limited; the license

only allows installation on a limited number of

computers; add-ons to the PASW require acquisition to

additional licenses. The licensing is not user friendly

(Harrington, et al., 2009).

3. Confusion among the

different versions

Because PASW is updated every year a number of

issues can occur with features and data formats are

available especially between the MAC and Windows

products

Table 4

Advantages and disadvantages of PASW from the student view

Advantages

1. Well known and supported Students would have relatively little difficulty in

obtaining support for their SPSS work from textbooks,

Internet resources, and other students.

2. Ease of use The graphical user interface provides the student with

quick access to the statistical routines needed for an

introductory course; student also has the ability to

customize PASW results including the display of

graphic output

3. Broad coverage All the statistical routines required by the introductory


statistics course would be available to the students

4. Availability of help The student has access to a large number of excellent

books that provide comprehensive information on using

PASW

Disadvantages

1. Cost At price point of almost $200 even for the Graduate

version of the PASW package, the cost is an issue for

student

2. Licensing complexity Although students would be able to use their purchased

package for the duration of the introductory statistics

course subsequent use of the package in graduate and

professional work would become a licensing problem


different versions

Students may try to purchase or borrow older versions

of PASW which could create issues for them with the

instructions in the selected introductory statistics

textbook

4. Lag in newer techniques "For academic use SPSS lags notably behind SAS, R

and even perhaps others that are on the more

mathematical rather than statistical side for modern data

analysis (e.g. robust and bootstrapping approaches

available easily conducted elsewhere are nonexistent or

very difficult to do, basic tests of analytical assumptions

are often not available)" (Harrington, et al., 2009)

Advantages and Disadvantages of Excel

The advantages and disadvantages for Excel are provided in Table 5 (instructor) and

Table 6 (student).

Table 5

Advantages and disadvantages of Excel from the instructor view

Advantages


1. Availability All of the labs in the University have the Microsoft

Office Package on them and therefore, access is always

available. Instructors don’t have to go through the

hassle of having “special” software installed on the

computers each semester.

2. Availability of Help On-line help is extensive and the package also has a

built in help function that is very user friendly.

3. Ease of Use Very hands on friendly and intuitive to use. The

dropdown menus make it easy to find things.

4. Add-Ins The software has a standard installation, but you can

also add-in data analysis tool packages, specifically to

do Statistical applications. Therefore, you don’t have to

know any coding or programming languages.

5. Coverage

6. Data Sets

The package includes all of the Statistical applications

that an introductory course needs.

Many authors are including data sets with the textbooks

that are already in Excel files and ready for analysis.

Also, many web sites that manage data sets are putting

them in a format that is easy to download as an Excel

file.

Disadvantages

1. Cost Although the package is available in all of the labs on

campus, an instructor would need to purchase the

software package for any home computers that they use.

2. Potential Calculation

Problems

The program doesn’t calculate the 3rd

quartile correctly

(Anderson, 2009). Problems with the calculations in

Excel have also been identified by McCullough and

Heiser (2008) and Yalta (2008).

3. Limitations of Data The number of data points is limited to x amount. In

terms of an introductory course this is not necessarily

an issue, but it can be when showing analysis of large

data sets. The limitations of Excel are provided by


Microsoft (2009a).

4. Functions Some of the advanced statistical functions are not

included in the package.

Table 6

Advantages and disadvantages of Microsoft’s Excel from the student view

Advantages

1. Availability All of the University labs have Microsoft Office

installed on them, so the students have access to Excel

everywhere on campus.

2. Cost There is no cost to the students if they use the

computers in the lab.

3. Availability of Help There is extensive on-line help and the package also

includes a help function that is easy to find information.

4. Textbook Many of the textbooks include instruction on the

functions in Excel, which allows students to follow

along and do practice problems on their own.

5. Data files

6. Applicability to other

Courses

Many of the textbooks are including data files that are

already in Excel format and also many web sites that

manage data sets are making the files available for

download in Excel format.

The use of Excel is becoming the standard in many

other areas of business instruction such as accounting,

finance and operations. Therefore, the students can use

the skills they learn in other courses as they work

through their programs.

Disadvantages

1. Customization The ability to customize the package is not very user


friendly. You can add macros using visual basic, but

this requires the knowledge of a computer programming

language.

2. Large Data Sets The limitations of Excel are provided by Microsoft

(2009a).


different versions

Because Excel is in a current transition from 2003 to

2007, students sometimes are working in one version

and being taught in another; this can be confusing to

them. Although the functions are all the same, where to

find them is different for each version.

Conclusion

This paper explored three popular software packages to determine their advantages and

disadvantages for use in an introductory business statistics course. By assessing these pros and

cons in terms of both the instructor and student perspective a better decision about which of these

package to choose can be made. Although any of the three packages would provide learners with

the ability to perform computations and display graphs and charts, each of these choices has its

own unique set of strengths and weaknesses. This report identified a number of assets and

liabilities for each of the three packages in Tables 1 thru 6. Because of its low cost,

computational and charting flexibility, interface familiarity, and wide availability the selection of

Excel is seen as the best choice. The availability factor for Excel includes not only its presence in

college computer labs and classrooms but also its wide use in businesses. After students

complete their business degrees and are employed in their fields, the availability of Excel in

these future workplaces will far exceed SPSS or R. By selecting Excel for use in the statistics

course, the instructor has added to the motivation for his or her students because in almost all of

their potential employment destinations, the former student will be able to use Excel on the job


for their data analysis needs. Consequently Excel is an excellent choice for instructors to use to

support their introductory statistics class.


References

Anderson, D. R. (2009). Essentials of modern business statistics (4th Ed. ed.). Eagan, MN:

Cengage South-Western.

Barnes, K. (2009). Skills Most Sought After by Employers Retrieved October 24, 2009, from

http://iccweb.ucdavis.edu/LAB/articles/Skills.htm

Department of Mathematics and Statistics at Vienna University. (n.d.). The R package for

statistical computing Retrieved October 24, 2009, from http://www.r-project.org/

Harrington, R., McLeod, P., & M.Clark. (2009). SPSS short course. Retrieved October 12, 2009,

from

http://www.unt.edu/rss/class/SPSS/course1.htm#VI.__Relative_Advantages_and_Disadv

anatges_

Journey Education Marketing, I. (2009). PASW Statistics Grad Pack 18.0 for Windows

(Formerly SPSS). Retrieved October 12, 2009, from

http://www.journeyed.com/item/SPSS/PASW+Statistics+Graduate+Pack/100966436?sS

RCCODE=GOOGLEBASE&utm_source=GoogleBase&utm_medium=Comp%2BEngin

es&utm_campaign=jce01

McCullough, B. D., & Heiser, D. A. (2008). On the accuracy of statistical procedures in

Microsoft Excel 2007. Computational Statistics and Data Analysis, 52(10), 4570-4578.

Microsoft Inc. (2009a). Excel specifications and limits Retrieved October 26, 2009, from

http://office.microsoft.com/en-us/Excel/HP100738491033.aspx

Microsoft Inc. (2009b). Microsoft Office Excel 2007 Retrieved October 25, 2009, from

http://office.microsoft.com/en-us/Excel/FX100487621033.aspx

SPSS Inc. (2009). SPSS an IBM company Retrieved October 24, 2009, from www.spss.com

Yalta, A. T. (2008). The accuracy of statistical distributions in Microsoft Excel 2007.

Computational Statistics & Data Analysis, 52(10), 4579-4586.

Zieffler, A., & Long, J. D. (n.d.). Basics of R. Retrieved October 12, 2009, from

http://docs.google.com/gview?a=v&q=cache%3AKNt87a_hJBAJ%3Awww.tc.umn.edu

%2F%7Ezief0002%2FNotes%2FRBasics.pdf+advantages+of+R&hl=en&gl=us&sig=AF

QjCNFNcPf8U4xtjQ3vC-qvzUcCqYod0w&pli=1

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