General Linear Model Within-Subjects Factors Measure: Errors Dependent Training_Time Variable Training_Time _1 2 Training_Time 2 3 Training_Time _3 Between-Subjects Factors Value Label N Self-Effiacy 1.00 Self-Effiacy HIGH 2.00 Self Effiacy 3 LOW Descriptive Statistics Self-Effiacy Mean Std. Deviation N Training Time 25% Self-Effiacy HIGH 15.5556 4.41902 9 Self Effiacy LOW 13.6667 2.51661 3 Total 15.0833 4.01040 12 Training Time 50% Self-Effiacy HIGH 7.7778 2.77389 Self Effiacy LOW 10.0000 4.35890 3 Total 8.3333 3.17185 12 Training Time 75% Self-Effiacy HIGH 7.7778 83333 9 Self Effiacy LOW 10.6667 1.15470 3 Total 8.5000 1.56670 12Player Training_Ti Training_Ti Training_Ti Self_Effiacy me 1 me 2 me 3 12.00 8.00 7.00 1.00 2 13.00 8.00 7.00 1.00 3 14.00 6.00 8.00 1.00 4 22.00 5.00 8.00 1.00 5 16.00 6.00 9.00 1.00 6 14.00 4.00 7.00 1.00 11.00 5.00 10.00 2.00 12.00 10.00 9.00 1.00 13.00 11.00 7.00 1.00 0 10 24.00 12.00 8.00 1.00 11 16.00 12.00 12.00 2.00 2 12 14.00 13.00 10.00 2.00SPSS |(Clrutput: Rh'lANDVA (Week: 4; Module: 4) A sports psychologist is working with a baseball team to determine if the implementation of a selfefcacy training program is effective in improving on the eld performance. Specically, the psychologist and coach want to improve the rate of elding errors on defense. The psychologist believes that by implementing the selfefcacy program, the elding errors will decrease. Based on previous research, there was a decrease, but that research did not include a before and after design, and it is not clear whether this effect will hold over time. Therefore, for this research, the psychologist has decided to collect data on players (n=12), measuring the number of elding errors in games as scored oicially by the scorekeeper. The researchers have decided that it would be a much more robust study to measure the elding errors following the first 25% of gains in the season immediately before implementing the training program, then assess the elding errors for the next 25% of the season following the training program, and again at the following 25% mark. The goal is to determine whether or not the training program is effective over time, and by collecting data points at the 25%, 50%, and ?5% marks, it will help them make decisions for the last 25% of the season Following the assignment instructions, use a repeated measures ANDVA statistical design using moclo'ctitious data to demonstrate how this research might be conducted The independent variable is the Self-Efficacy Training Program. The dependent variable is the Field Performance. The HN: Self-efficacy training program does not affect performance in field performance The HO: Self-efficacy training program is effective in improving on the field performance.Multivariate Tests" Effect Value F Hypothesis of Error df Sig Training_Time Pillai's Trace 642 8.080 2.000 9.000 010 Wilks' Lambda .358 8.080 2.000 9.000 .010 Hotelling's Trace 1.796 8.080 2.000 9.000 010 Roy's Largest Root 1.796 8.080 2.000 9.000 010 Training_Time * Pillai's Trace .251 1.506 2.000 9.000 .273 Self_Effiacy Wilks' Lambda 749 1.506 2.000 9.000 273 Hotelling's Trace 335 1.506 2.000 9.000 273 Roy's Largest Root .335 1.506 2.000 9.000 .273 a. Design: Intercept + Self_Effiacy Within Subjects Design: Training_Time b. Exact statistic Mauchly's Test of Sphericity" Measure: Errors Epsilon Approx. Chi- Greenhouse- Within Subjects Effect Mauchly's W Square df Sig Geisser Huynh-Feldt Lower-bound Training_Time 816 1.833 2 400 844 1.000 500 Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix. a. Design: Intercept + Self_Effiacy Within Subjects Design: Training_Time b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table.Mauchly's Test of Sphericity" Measure: Errors Epsilon Approx. Chi- Greenhouse- Within Subjects Effect Mauchly's W Square df Sig. Geissel Huynh-Feldt Lower-bound Training_Time .816 1.833 2 400 844 1.000 500 Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix. a. Design: Intercept + Self_Effiacy Within Subjects Design: Training_Time b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Within-Subjects Effects table Tests of Within-Subjects Effects Measure: Errors Type Ill Sum of Source Squares df Mean Square F Sig Training_Time Sphericity Assumed 185.685 2 92.843 11.943 <.001 greenhouse-geisser huynh-feldt lower-bound training_time sphericity assumed self_effiacy .194 error of within-subjects contrasts measure: errors type ill sum source squares df mean square f sig. linear quadratic .025 tests between-subjects effects transformed variable: average intercept>