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Assignment 2: SPSS Tutorial on Data Handling

Problem Scenario

Three professors at a private college, Fit University, studied the association between physical exercise and optimism. Fit U was renowned for its extraordinary fitness program, facilities, and equipment. Coach Neely, the head coach, noticed a trend over the years. Fit U students who exercised regularly seemed to have better attitudes than students from other colleges who didn’t get regular exercise. Coach Neely asked psychologist Dr. Jane Doe to design a study. In the meantime, Dr. Buck, a business professor, decided to invest in a gym-equipment business. He collaborated with them as well. Each had real interest in the results of the study.

For participants, they got a random sample of male and female students in all four levels from freshman, sophomores, juniors, and seniors. After some discussion, they decided to collect data on the following types of exercise available on campus.

Variable Explanation Measurement Scale

Natatt Attitude about nature on a scale from 1–100, where the higher the number, the more the respondent likes nature. Scale (Interval)

Trail Minutes of working out weekly on the Physical Phun Nature Trail Scale (Ratio)

Runner Runner was defined as running over a mile at least once a week. 1 = no, 2 = yes Nominal

Yoga Hours of practicing yoga per week Scale (Ratio)

Collegeyr Year in college: 1 = freshman, 2 = sophomore, 3 = junior, 4 = senior Ordinal

Class Physical fitness class based on accumulated points Ordinal

Bench Highest weight participant is able to bench-press Scale (Ratio)

Squats Total number of consecutive squats participant is able to do Scale (Ratio)

Fortydash Seconds of times to dash 40 yards Scale (Ratio)

PTS Total fitness points earned Scale (Ratio)

Gennum Gender by number. 1 = male, 2 = female Nominal

Genword Gender in words Nominal

Before Tx Optimism score before treatment, measured by a validated survey Scale (interval)

After Tx Optimism score after treatment, measured by a validated survey Scale (interval)

Spreadsheet Basics

We’re going to use the statistical software, Statistical Package for the Social Sciences or SPSS, to work with data in this class. It analyzes data on a spreadsheet. The data must be entered on the spreadsheet correctly for the analyses to be correct (Cronk, 2008; Pallant, 2001). The following refers to the data R7031 Module 1 data, which you can download from Doc Sharing.

The data go in vertical columns. So the top of each column is labeled with the variable name. Research participants are listed or implied in the first column. Once all the variables have been entered in the columns, the data from each research participant appear in that participant’s corresponding row when data on each variable are collected from all participants, as it is in our case.

There are several ways to get data into an SPSS spreadsheet. One, you can enter the data by hand onto a blank SPSS spreadsheet. Note that until you tell the software what your data are (the name of the variable, whether they occur as words or numbers, measurement scales, etc.), the labels on the tops of the columns (VAR001) appear automatically.

Two, you can import the data from an Excel file so we include a word or two about Excel, another spreadsheet program that initially seems more user-friendly than SPSS. To do this, save and close the Excel file if it is open. It cannot be imported into SPSS if it is open. Then in SPSS, go to File/Open/Data and the window shown in Figure 2 appears. Where it says SPSS (*.sav), scroll down to Excel (*.xls) and click it; this will show your Excel files. Click on the one you want.

When you do that, you will see the window in Figure 3 if you have labeled your variables in the first row in your Excel file. Click okay and SPSS will automatically transfer your labels. However, we have to tell SPSS about the data so it will allow us to do the statistics we’d like to do.

Figure 4 shows what you should be seeing. Notice that there are two tabs at the lower left-hand corner of the spreadsheet. The current tab is Data View. This is your view of the data.

Go to the lower left-hand corner of the SPSS spreadsheet and click on the Variable View tab. It will look like Figure 5. We make some changes in Variable View.

SPSS Variable View Name Column

In the first Name column under Variable View, the variable labels you used in Excel appear. SPSS will cut off long names and those with spaces in them will not appear. Also, avoid using numbers to name variables. SPSS can do some strange things to those labels!

I have coded ours so SPSS does not change them. Here is the explanation of each variable. As you read through them, decide which of the 4 measurement scales they are most likely to fall under.

Natatt = Attitude about nature on a scale from 1–100, where the higher the number, the more the respondent likes nature.

Trail = minutes of working out weekly on the Physical Phun Nature Trail

Runner = whether the participant is a runner or not. 1 = no, 2 = yes

Yoga = minutes of practicing yoga per week

Collegeyr = what year the participant is in college. 1 = freshman, 2 = sophomore, 3 = junior, 4 = senior

Class = physical fitness class

Bench = highest weight participant is able to bench-press

Squats = total number of consecutive squats participant is able to do

Fortydash = seconds of time it takes to dash 40 yards

PTS = total fitness points earned

Gennum = gender by number. 1 = male, 2 = female

Genword = gender in words

Before Tx = optimism score before treatment, measured by a validated survey

After Tx = optimism score after treatment, measured by a validated survey

SPSS Variable View Type Column

In the second column, Type, you tell SPSS if you have entered words or numbers for the data. In SPSS, words = string, and numbers = numeric.

In the Type column, Class and genwords should be string variables. The rest of the variables should be numeric. If they are not, click on the errant cell. A little gray box with 3 dots appears. Click on it to see the menu of options and choose the appropriate one.

Figure 6.

Measurement Scale of the Variables

Scale: Natatt, Trail, Yoga, Bench, Squats, Fortydash, PTS, Before Tx, After Tx

Ordinal: Collegeyr, Class

Nominal: Runner, Gennum, Genword

SPSS Variable View Values Column

In the 6th column, Values, you can enter the numbers that go with the levels of your ordinal and nominal variables.

For example, go the cell in the Values column across from genum: 1 = male, 2 = female. Click on the cell and then on the little gray box. The window shown in Figure 7 will appear. Where is says Value, type a 1. Where it says Label, type in male. Click Add.

Figure 7.

Do the same for 2 and female, then click OK.

Do the same for the variable runner (1 = no, 2 = yes) and Collegeyr (1 = freshman, 2 = sophomore, 3 = junior, 4 = senior).

SPSS Variable View Label Column

Finally, go to the 5th column, Label. Here you can write in longer words or phrases to remind you what the variables are. These labels will appear throughout the analysis and can be very helpful.

Fill in the labels as you like. When you are done, your Variable View should look something like Figure 8.

Figure 8.

Read through the final section on type of research questions before you participate in the SPSS tutorial with your instructor or go through the prerecorded WebEx session yourself. Remember, statistics are done and research is conducted to answer questions. Before trying each demonstrated technique, identify the question it answers. It’s great practice for your dissertation

"If you study to remember, you will forget, but, If you study to understand, you will remember!"

Beceriler: Eğitim & Özel Ders, Matematik, İstatistik

Daha fazlasını görün: r7031 research scenario, working gym, see years, work values, very jane, value options, use case types, use case tutorial, use case module, use case levels, use case include example, university sciences, types research design, type use case, two string problem, tutorial words, tutorial use case, tutorial top, tutorial numbers, tutorial case problem, top tutorial, top statistics colleges, top statistics, top levels, top coded

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