A Step by Step Guide for SPSS and Exercise Studies

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Statistical tests 149 Dialog box 97 measure intraclass correlation is not surprising, because it indicates that there are significant differences in the scores of different gymnasts (i.e., differences across the rows of Figure 44). The single measure intraclass correlation shows the reliability if only one judge was used. Usually, this reliability is lower than the reliability obtained from multiple judges (i.e., average measure intraclass correlation). Table 57
150 Statistical tests Nonparametric Tests/Chi-square This test is employed to compare two or more categories of one or more variables. For example, you may want to examine whether a sample of 100 pupils differ in their choice of favourite football club. After carrying out a frequency count, you find out that 32 pupils support club A, 26 support club B, 19 support club C, 14 support club D, and 9 support club E. In the data file you can create a variable with 100 cases (rows) that will represent the club preference of each pupil. Alternatively, you can create another variable (clubs) with five rows. Type in the total number of preferences for each of the five clubs, and then use the weight cases option of the Data menu to indicate that each row represents a total score rather than an individual case (Figure 45). Move the clubs variable into the Test variable list (Dialog box 98). Use Options to ask for descriptive statistics and specify how to handle missing values. If you want to restrict the comparison to, say, the first three clubs only (A, B, and C), select use specified range under Expected Range and type 1 and 3 as the Lower and Upper values. Then click OK. The output in Table 58 shows the observed number of preferences for each club. If there were no significant differences in club preference, the expected number of preferences for each club would have been 20. The chi-square test examines the significance of the differences between the expected and the actual (observed) preferences. The results show that the chi-square value (x 2 (4) ˆ 16.9) is significant (p ˆ .002), which means that there is a significant difference in club preference (Table 59). Club A is the most popular club and club E is the least popular. Residual represent the difference between the observed and expected frequencies. For a chi-square analysis, a relatively large sample size is Dialog box 98
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A Step-by-Step Guide to SPSS for Sp
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First published 2001 by Routledge 1
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Contents Preface Acknowledgements x
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Contents 4 Chart and table options
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Preface This book intends to fill i
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Acknowledgements The comments and s
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2 Introduction variety of options a
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4 Introduction Data Entry Each row
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6 Introduction Dialog box 3 Dialog
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8 Data handling Dialog box 5 Dialog
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10 Data handling Dialog box 8 Dialo
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12 Data handling Dialog box 11 Dial
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14 Data handling Dialog box 14 Tabl
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16 Data handling Dialog box 16 numb
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18 Data handling Dialog box 18 Expo
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20 Data handling for any analysis t
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22 Data handling Show/Hide These op
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24 Data handling Dialog box 21 asce
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26 Data handling Merge File (Add Ca
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28 Data handling Dialog box 25 Tabl
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30 Data handling Dialog box 27 Figu
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32 Data handling Figure 13 Dialog b
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42 Data handling Figure 16 size of
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3 Statistical tests Analyze A varie
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46 Statistical tests Table 5 Dialog
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48 Statistical tests Table 6 for ea
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50 Statistical tests Table 7 Dialog
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52 Statistical tests Dialog box 53
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54 Statistical tests Table 9 (i.e.,
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58 Statistical tests Table 12 Table
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60 Statistical tests Custom Tables/
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64 Statistical tests Table 16 Dialo
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66 Statistical tests How to carry o
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Table 20
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230 Chart and table options Table 7
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Table 75
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5 Miscellaneous options Utilities V
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246 Miscellaneous options Dialog bo
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248 Miscellaneous options Format Di
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250 Suggested reading Pedhazur, E.
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252 Index discriminant analysis 2,
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A Step by Step Guide for SPSS and Exercise Studies

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