One Way ANOVA with Tukey Post hoc. Case Processing Summary

EXAMINE VARIABLES=Score BY Group /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Group One Way ANOVA with Tukey Post hoc Case Processing Summary Score Cases Valid Missing Total Group N Percent N Percent N Percent 1 5 100.0% 0.0% 5 100.0% 2 5 100.0% 0.0% 5 100.0% 3 5 100.0% 0.0% 5 100.0% 4 5 100.0% 0.0% 5 100.0% Descriptives Score Group Statistic Std. Error 1 Mean 6.00 1.140 95% Confidence Lower Bound 2.83 Interval for Mean Upper Bound 9.17 2 5% Trimmed Mean 6.00 Median 6.00 Variance 6.500 Std. Deviation 2.550 Minimum 3 Maximum 9 Range 6 Interquartile Range 5 Skewness.000.913 Kurtosis -2.260 2.000 Mean 9.00.548 95% Confidence Lower Bound 7.48 Interval for Mean Upper Bound 10.52 5% Trimmed Mean 8.94 Median 9.00

3 4 Variance 1.500 Std. Deviation 1.225 Minimum 8 Maximum 11 Range 3 Interquartile Range 2 Skewness 1.361.913 Kurtosis 2.000 2.000 Mean 7.00.707 95% Confidence Lower Bound 5.04 Interval for Mean Upper Bound 8.96 5% Trimmed Mean 7.00 Median 7.00 Variance 2.500 Std. Deviation 1.581 Minimum 5 Maximum 9 Range 4 Interquartile Range 3 Skewness.000.913 Kurtosis -1.200 2.000 Mean 2.40.748 95% Confidence Lower Bound.32 Interval for Mean Upper Bound 4.48 5% Trimmed Mean 2.33 Median 2.00 Variance 2.800 Std. Deviation 1.673 Minimum 1 Maximum 5 Range 4 Interquartile Range 3 Skewness 1.089.913 Kurtosis.536 2.000 Score Kolmogorov-Smirnov(a) Tests of Normality Shapiro-Wilk Group Statistic df Sig. Statistic df Sig. 1.184 5.200(*).944 5.692 2.300 5.161.833 5.146 3.136 5.200(*).987 5.967 4.201 5.200(*).881 5.314 * This is a lower bound of the true significance. a Lilliefors Significance Correction

Test the Shapiro-Wilk statistic (SW) @.01 Score UNIANOVA Score BY Group /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /POSTHOC = Group ( TUKEY ) /PRINT = DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA = ALPHA(.05) /DESIGN = Group.

Univariate Analysis of Variance Between-Subjects Factors Group N 1 5 2 5 3 5 4 5 Dependent Variable: Score Descriptive Statistics Group Mean Std. Deviation N 1 6.00 2.550 5 2 9.00 1.225 5 3 7.00 1.581 5 4 2.40 1.673 5 Total 6.10 2.972 20 Levene's Test of Equality of Error Variances(a) Dependent Variable: Score F df1 df2 Sig. 1.367 3 16.289 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a Design: Intercept+Group HOV test at.01. Dependent Variable: Score Tests of Between-Subjects Effects Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Corrected Model 114.600(a) 3 38.200 11.489.000.683 Intercept 744.200 1 744.200 223.820.000.933 Group 114.600 3 38.200 11.489.000.683 Error 53.200 16 3.325 Total 912.000 20 Corrected Total 167.800 19 a R Squared =.683 (Adjusted R Squared =.624) Use the row with the name of the IV to interpret the ANOVA results. A statistically significant difference amongthe means is evident.

Post Hoc Tests Group Multiple Comparisons Dependent Variable: Score Tukey HSD (I) Group 1 2 3 Mean 95% Confidence Interval Difference (J) Group (I-J) Std. Error Sig. Lower Bound Upper Bound 2-3.00 1.153.082-6.30.30 3-1.00 1.153.822-4.30 2.30 4 3.60(*) 1.153.030.30 6.90 1 3.00 1.153.082 -.30 6.30 3 2.00 1.153.339-1.30 5.30 4 6.60(*) 1.153.000 3.30 9.90 1 1.00 1.153.822-2.30 4.30 2-2.00 1.153.339-5.30 1.30 4 4.60(*) 1.153.005 1.30 7.90 4 1-3.60(*) 1.153.030-6.90 -.30 2-6.60(*) 1.153.000-9.90-3.30 3-4.60(*) 1.153.005-7.90-1.30 Based on observed means. * The mean difference is significant at the.05 level. Tukey post hoc analysis to determine where the differences exist between the groups. Homogeneous Subsets Tukey HSD Score Subset Group N 1 2 4 5 2.40 1 5 6.00 3 5 7.00 2 5 9.00 Sig. 1.000.082 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) = 3.325. a Uses Harmonic Mean Sample Size = 5.000. b Alpha =.05.

A priori ANOVA EXAMINE VARIABLES=Score BY Group /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Group Case Processing Summary Score Cases Valid Missing Total Group N Percent N Percent N Percent 1 5 100.0% 0.0% 5 100.0% 2 5 100.0% 0.0% 5 100.0% 3 5 100.0% 0.0% 5 100.0% 4 5 100.0% 0.0% 5 100.0% Descriptives Score Group Statistic Std. Error 1 Mean 6.00 1.140 95% Confidence Lower Bound 2.83 Interval for Mean Upper Bound 9.17 2 5% Trimmed Mean 6.00 Median 6.00 Variance 6.500 Std. Deviation 2.550 Minimum 3 Maximum 9 Range 6 Interquartile Range 5 Skewness.000.913 Kurtosis -2.260 2.000 Mean 9.00.548 95% Confidence Lower Bound 7.48 Interval for Mean Upper Bound 10.52 5% Trimmed Mean 8.94 Median 9.00

Score UNIANOVA Score BY Group /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /POSTHOC = Group ( TUKEY ) /PRINT = DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA = ALPHA(.05) /DESIGN = Group.

Univariate Analysis of Variance Between-Subjects Factors Group N 1 5 2 5 3 5 4 5 Dependent Variable: Score Descriptive Statistics Group Mean Std. Deviation N 1 6.00 2.550 5 2 9.00 1.225 5 3 7.00 1.581 5 4 2.40 1.673 5 Total 6.10 2.972 20 Levene's Test of Equality of Error Variances(a) Dependent Variable: Score F df1 df2 Sig. 1.367 3 16.289 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a Design: Intercept+Group Dependent Variable: Score Tests of Between-Subjects Effects Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Corrected Model 114.600(a) 3 38.200 11.489.000.683 Intercept 744.200 1 744.200 223.820.000.933 Group 114.600 3 38.200 11.489.000.683 Error 53.200 16 3.325 Total 912.000 20 Corrected Total 167.800 19 a R Squared =.683 (Adjusted R Squared =.624) ONEWAY Score BY Group /CONTRAST= 1-2 1 0 /CONTRAST= 0 1-1 0 /MISSING ANALYSIS.

Contrast Coefficients Group Contrast 1 2 3 4 1 1-2 1 0 2 0 1-1 0 Contrast Tests Score Assume equal variances Contrast Value of Contrast Std. Error t df Sig. (2-tailed) 1-5.00 1.997-2.503 16.024 2 2.00 1.153 1.734 16.102 Does not assume equal 1-5.00 1.732-2.887 10.651.015 variances 2 2.00.894 2.236 7.529.058 The t-tests serve as the a priori analyses after a significant ANOVA. Because the HOV test was not significant, assume equal variances.

Factorial ANOVA with No Interaction EXAMINE VARIABLES=gpaimpr BY gender method /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Notes Output Created 20-DEC-2007 10:17:55 Comments Input Missing Value Handling Syntax Data C:\Documents and Settings\BalkinRick\Desktop\613\SPS S data\windows\lesson 25\Lesson 25 Data File 1.sav Active Dataset DataSet4 Filter <none> Weight <none> Split File <none> N of Rows in Working Data File 60 Definition of Missing Cases Used User-defined missing values for dependent variables are treated as missing. Statistics are based on cases with no missing values for any dependent variable or factor used. EXAMINE VARIABLES=gpaimpr BY gender method /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Resources Elapsed Time 0:00:03.76

Gender Case Processing Summary Change in GPA Cases Valid Missing Total Gender N Percent N Percent N Percent Men 30 100.0% 0.0% 30 100.0% Women 30 100.0% 0.0% 30 100.0% Descriptives Change in GPA Gender Statistic Std. Error Men Mean.3800.04928 95% Confidence Lower Bound.2792 Interval for Mean Upper Bound.4808 Women 5% Trimmed Mean.3741 Median.3500 Variance.073 Std. Deviation.26993 Minimum -.10 Maximum 1.00 Range 1.10 Interquartile Range.41 Skewness.357.427 Kurtosis -.373.833 Mean.1933.03447 95% Confidence Interval for Mean Lower Bound.1228 Upper Bound.2638 5% Trimmed Mean.1870 Median.2000 Variance.036 Std. Deviation.18880 Minimum -.10 Maximum.60 Range.70 Interquartile Range.33 Skewness.527.427 Kurtosis -.713.833

Tests of Normality Change in GPA Kolmogorov-Smirnov(a) Shapiro-Wilk Gender Statistic df Sig. Statistic df Sig. Men.117 30.200(*).972 30.603 Women.156 30.060.924 30.033 * This is a lower bound of the true significance. a Lilliefors Significance Correction Tests for normality of GPA change across gender at.01. Change in GPA

Note-Taking methods Case Processing Summary Change in GPA Cases Valid Missing Total Note-Taking methods N Percent N Percent N Percent Method 1 20 100.0% 0.0% 20 100.0% Method 2 20 100.0% 0.0% 20 100.0% Control 20 100.0% 0.0% 20 100.0% Descriptives Change in GPA Note-Taking methods Statistic Std. Error Method 1 Mean.2525.04887 95% Confidence Lower Bound.1502 Interval for Mean Upper Bound.3548 Method 2 Control 5% Trimmed Mean.2361 Median.2250 Variance.048 Std. Deviation.21853 Minimum.00 Maximum.80 Range.80 Interquartile Range.38 Skewness.719.512 Kurtosis.373.992 Mean.4725.05566 95% Confidence Lower Bound.3560 Interval for Mean Upper Bound.5890 5% Trimmed Mean.4694 Median.5000 Variance.062 Std. Deviation.24893 Minimum.00 Maximum 1.00 Range 1.00 Interquartile Range.34 Skewness.049.512 Kurtosis -.054.992 Mean.1350.03287 95% Confidence Interval for Mean Lower Bound.0662 Upper Bound.2038 5% Trimmed Mean.1333

Median.1000 Variance.022 Std. Deviation.14699 Minimum -.10 Maximum.40 Range.50 Interquartile Range.24 Skewness.231.512 Kurtosis -.597.992 Change in GPA Tests of Normality Kolmogorov-Smirnov(a) Shapiro-Wilk Note-Taking methods Statistic df Sig. Statistic df Sig. Method 1.126 20.200(*).916 20.081 Method 2.154 20.200(*).971 20.766 Control.144 20.200(*).952 20.392 * This is a lower bound of the true significance. a Lilliefors Significance Correction Tests for normality of GPA change across method at.01.

Change in GPA Boxplots UNIANOVA gpaimpr BY gender method /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /POSTHOC = method ( TUKEY ) /PLOT = PROFILE( method*gender ) /PRINT = DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA = ALPHA(.05) /DESIGN = gender method gender*method.

Univariate Analysis of Variance Between-Subjects Factors Gender Note-Taking methods Value Label N 1 Men 30 2 Women 30 1 Method 1 20 2 Method 2 20 3 Control 20 Descriptive Statistics Dependent Variable: Change in GPA Gender Note-Taking methods Mean Std. Deviation N Men Method 1.3350.22858 10 Method 2.6400.17764 10 Control.1650.14916 10 Total.3800.26993 30 Women Method 1.1700.18288 10 Method 2.3050.19214 10 Control.1050.14615 10 Total.1933.18880 30 Total Method 1.2525.21853 20 Method 2.4725.24893 20 Control.1350.14699 20 Total.2867.24938 60 Levene's Test of Equality of Error Variances(a) Dependent Variable: Change in GPA F df1 df2 Sig..575 5 54.719 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a Design: Intercept+gender+method+gender * method HOV test at.01

Tests of Between-Subjects Effects Dependent Variable: Change in GPA Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Corrected Model 1.889(a) 5.378 11.463.000.515 Intercept 4.931 1 4.931 149.582.000.735 gender.523 1.523 15.856.000.227 method 1.174 2.587 17.809.000.397 gender * method.193 2.096 2.921.062.098 Error 1.780 54.033 Total 8.600 60 Corrected Total 3.669 59 a R Squared =.515 (Adjusted R Squared =.470) First, look at the interaction effect--it is not signficant. So, main effects can be interpreted. The main effects are denoted by the rows with the names of the IVs. Each of the main effects is statistically significant. Because Method has more than two levels, a Tukey post hoc is needed to determine where the differences lie. Post Hoc Tests Note-Taking methods Dependent Variable: Change in GPA Tukey HSD Multiple Comparisons (I) Note-Taking methods Method 1 Method 2 Control Based on observed means. * The mean difference is significant at the.05 level. Mean 95% Confidence Interval Difference (J) Note-Taking methods (I-J) Std. Error Sig. Lower Bound Upper Bound Method 2 -.2200(*).05741.001 -.3584 -.0816 Control.1175.05741.111 -.0209.2559 Method 1.2200(*).05741.001.0816.3584 Control.3375(*).05741.000.1991.4759 Method 1 -.1175.05741.111 -.2559.0209 Method 2 -.3375(*).05741.000 -.4759 -.1991

Homogeneous Subsets Tukey HSD Change in GPA Subset Note-Taking methods N 1 2 Control 20.1350 Method 1 20.2525 Method 2 20.4725 Sig..111 1.000 Means for groups in homogeneous subsets are displayed. Based on Type III Sum of Squares The error term is Mean Square(Error) =.033. a Uses Harmonic Mean Sample Size = 20.000. b Alpha =.05.

Profile Plots I have included this plot for instructional purposes, as it is not necessary since the interaction effect was not significant. Note the similarity in the patterns of responses.

Factorial ANOVA with Significant Interaction EXAMINE VARIABLES=gpaimpr BY gender method /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Gender Case Processing Summary Change in GPA Cases Valid Missing Total Gender N Percent N Percent N Percent Men 30 100.0% 0.0% 30 100.0% Women 30 100.0% 0.0% 30 100.0% Descriptives Change in GPA Gender Statistic Std. Error Men Mean.2683.03663 95% Confidence Lower Bound.1934 Interval for Mean Upper Bound.3433 Women 5% Trimmed Mean.2611 Median.2500 Variance.040 Std. Deviation.20064 Minimum -.10 Maximum.80 Range.90 Interquartile Range.30 Skewness.518.427 Kurtosis.377.833 Mean.3050.05341 95% Confidence Lower Bound.1958 Interval for Mean Upper Bound.4142 5% Trimmed Mean.2907 Median.2250 Variance.086 Std. Deviation.29254

Minimum -.10 Maximum 1.00 Range 1.10 Interquartile Range.53 Skewness.594.427 Kurtosis -.539.833 Tests of Normality Kolmogorov-Smirnov(a) Shapiro-Wilk Gender Statistic df Sig. Statistic df Sig. Change in GPA Men.137 30.155.968 30.487 Women.158 30.053.921 30.029 a Lilliefors Significance Correction

Change in GPA Note-Taking methods Case Processing Summary Change in GPA Cases Valid Missing Total Note-Taking methods N Percent N Percent N Percent Method 1 20 100.0% 0.0% 20 100.0% Method 2 20 100.0% 0.0% 20 100.0% Control 20 100.0% 0.0% 20 100.0%

Descriptives Change in GPA Note-Taking methods Statistic Std. Error Method 1 Mean.2525.04887 95% Confidence Lower Bound.1502 Interval for Mean Upper Bound.3548 Method 2 Control 5% Trimmed Mean.2361 Median.2250 Variance.048 Std. Deviation.21853 Minimum.00 Maximum.80 Range.80 Interquartile Range.38 Skewness.719.512 Kurtosis.373.992 Mean.4725.05566 95% Confidence Lower Bound.3560 Interval for Mean Upper Bound.5890 5% Trimmed Mean.4694 Median.5000 Variance.062 Std. Deviation.24893 Minimum.00 Maximum 1.00 Range 1.00 Interquartile Range.34 Skewness.049.512 Kurtosis -.054.992 Mean.1350.03287 95% Confidence Interval for Mean Lower Bound.0662 Upper Bound.2038 5% Trimmed Mean.1333 Median.1000 Variance.022 Std. Deviation.14699 Minimum -.10 Maximum.40 Range.50 Interquartile Range.24 Skewness.231.512 Kurtosis -.597.992

Change in GPA Tests of Normality Kolmogorov-Smirnov(a) Shapiro-Wilk Note-Taking methods Statistic df Sig. Statistic df Sig. Method 1.126 20.200(*).916 20.081 Method 2.154 20.200(*).971 20.766 Control.144 20.200(*).952 20.392 * This is a lower bound of the true significance. a Lilliefors Significance Correction Change in GPA Boxplots

UNIANOVA gpaimpr BY gender method /METHOD = SSTYPE(3) /INTERCEPT = INCLUDE /PLOT = PROFILE( method*gender ) /PRINT = DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA = ALPHA(.05) /DESIGN = gender method gender*method. Univariate Analysis of Variance Between-Subjects Factors Gender Note-Taking methods Value Label N 1 Men 30 2 Women 30 1 Method 1 20 2 Method 2 20 3 Control 20 Descriptive Statistics Dependent Variable: Change in GPA Gender Note-Taking methods Mean Std. Deviation N Men Method 1.3350.22858 10 Method 2.3050.19214 10 Control.1650.14916 10 Total.2683.20064 30 Women Method 1.1700.18288 10 Method 2.6400.17764 10 Control.1050.14615 10 Total.3050.29254 30 Total Method 1.2525.21853 20 Method 2.4725.24893 20 Control.1350.14699 20 Total.2867.24938 60 Levene's Test of Equality of Error Variances(a) Dependent Variable: Change in GPA F df1 df2 Sig..575 5 54.719 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a Design: Intercept+gender+method+gender * method

Profile Plots The interaction effect is plotted to demonstrate the discrepancy among the groups. UNIANOVA gpaimpr BY gender method /emmeans=table(gender*method) comp(method). SPSS code for analyzing simple effects.

Estimated Marginal Means Gender * Note-Taking methods Estimates Dependent Variable: Change in GPA 95% Confidence Interval Gender Note-Taking methods Mean Std. Error Lower Bound Upper Bound Men Method 1.335.057.220.450 Method 2.305.057.190.420 Control.165.057.050.280 Women Method 1.170.057.055.285 Method 2.640.057.525.755 Control.105.057 -.010.220 Dependent Variable: Change in GPA Pairwise Comparisons 95% Confidence Interval for Mean Difference(a) Gender (I) Note-Taking methods (J) Note-Taking methods Difference (I-J) Std. Error Sig.(a) Lower Bound Upper Bound Men Method 1 Method 2.030.081.713 -.133.193 Control.170(*).081.041.007.333 Women Method 2 Control Method 1 Method 2 Control Method 1 -.030.081.713 -.193.133 Control.140.081.090 -.023.303 Method 1 -.170(*).081.041 -.333 -.007 Method 2 -.140.081.090 -.303.023 Method 2 -.470(*).081.000 -.633 -.307 Control.065.081.427 -.098.228 Method 1.470(*).081.000.307.633 Control.535(*).081.000.372.698 Method 1 -.065.081.427 -.228.098 Method 2 -.535(*).081.000 -.698 -.372 Based on estimated marginal means * The mean difference is significant at the.050 level. a Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments). SPSS runs the post hoc tests before the tests for simple effects. Analyze simple effects first. Note that the simple effects (below)show statistical significance for women, but not men. Thus, we only need to look at post hoc tests for women.

Univariate Tests Dependent Variable: Change in GPA Gender Men Women Sum of Squares df Mean Square F Sig. Contrast.165 2.082 2.498.092 Error 1.780 54.033 Contrast 1.705 2.852 25.855.000 Error 1.780 54.033 Each F tests the simple effects of Note-Taking methods within each level combination of the other effects shown. These tests are based on the linearly independent pairwise comparisons among the estimated marginal means.

EXAMINE VARIABLES=time1 time2 time3 time4 /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Case Processing Summary Repeated Measures ANOVA Cases Valid Missing Total N Percent N Percent N Percent time1 30 100.0% 0.0% 30 100.0% time2 30 100.0% 0.0% 30 100.0% time3 30 100.0% 0.0% 30 100.0% time4 30 100.0% 0.0% 30 100.0% Descriptives time1 time2 Statistic Std. Error Mean 65.80 1.685 95% Confidence Lower Bound 62.35 Interval for Mean Upper Bound 69.25 5% Trimmed Mean 66.00 Median 67.50 Variance 85.131 Std. Deviation 9.227 Minimum 46 Maximum 81 Range 35 Interquartile Range 12 Skewness -.335.427 Kurtosis -.510.833 Mean 65.43 1.951 95% Confidence Lower Bound 61.44 Interval for Mean Upper Bound 69.42 5% Trimmed Mean 65.63 Median 65.50 Variance 114.185 Std. Deviation 10.686 Minimum 41

time3 time4 Maximum 85 Range 44 Interquartile Range 12 Skewness -.004.427 Kurtosis.254.833 Mean 63.10 1.951 95% Confidence Interval for Mean Lower Bound 59.11 Upper Bound 67.09 5% Trimmed Mean 63.11 Median 62.00 Variance 114.162 Std. Deviation 10.685 Minimum 42 Maximum 84 Range 42 Interquartile Range 9 Skewness.362.427 Kurtosis.121.833 Mean 61.93 2.294 95% Confidence Interval for Mean Lower Bound 57.24 Upper Bound 66.63 5% Trimmed Mean 61.69 Median 60.00 Variance 157.926 Std. Deviation 12.567 Minimum 35 Maximum 91 Range 56 Interquartile Range 15 Skewness.456.427 Kurtosis.210.833 Kolmogorov-Smirnov(a) Tests of Normality Shapiro-Wilk Statistic df Sig. Statistic df Sig. time1.094 30.200(*).963 30.364 time2.136 30.165.962 30.358 time3.170 30.026.936 30.070 time4.137 30.158.966 30.432 * This is a lower bound of the true significance. a Lilliefors Significance Correction Note that normality tests are run without a factor.

time1 time2

time3

time4

GLM time1 time2 time3 time4 /WSFACTOR = time 4 Polynomial /METHOD = SSTYPE(3) /PRINT = DESCRIPTIVE ETASQ /CRITERIA = ALPHA(.05) /WSDESIGN = time.

General Linear Model Within-Subjects Factors Measure: MEASURE_1 Dependent time Variable 1 time1 2 time2 3 time3 4 time4 Descriptive Statistics Mean Std. Deviation N time1 65.80 9.227 30 time2 65.43 10.686 30 time3 63.10 10.685 30 time4 61.93 12.567 30 Multivariate Tests(b) Partial Eta Effect Value F Hypothesis df Error df Sig. Squared time Pillai's Trace.382 5.567(a) 3.000 27.000.004.382 Wilks' Lambda.618 5.567(a) 3.000 27.000.004.382 Hotelling's Trace.619 5.567(a) 3.000 27.000.004.382 Roy's Largest Root.619 5.567(a) 3.000 27.000.004.382 a Exact statistic b Design: Intercept Within Subjects Design: time Measure: MEASURE_1 Mauchly's Test of Sphericity(b) Epsilon(a) Within Subjects Effect Mauchly's W Approx. Chi- Square df Sig. Greenhouse- Geisser Huynh-Feldt Lower-bound time.483 20.169 5.001.698.753.333 Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix. a 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. b Design: Intercept Within Subjects Design: time The sphericity assumption is not met. Additionally, E <.70. So, ANOVA results should be analyzed using Greenhouse-Geisser analysis below.

Measure: MEASURE_1 Source time Error(time) Tests of Within-Subjects Effects Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Sphericity Assumed 310.733 3 103.578 7.664.000.209 Greenhouse-Geisser 310.733 2.094 148.410 7.664.001.209 Huynh-Feldt 310.733 2.260 137.483 7.664.001.209 Lower-bound 310.733 1.000 310.733 7.664.010.209 Sphericity Assumed 1175.767 87 13.515 Greenhouse-Geisser 1175.767 60.719 19.364 Huynh-Feldt 1175.767 65.545 17.938 Lower-bound 1175.767 29.000 40.544 Since the Greenhouse-Geisser results are significant, post hoc analysis is necessary. A Tukey post hoc can be conducted by dependentt-tests. Measure: MEASURE_1 Source time Error(time) Tests of Within-Subjects Contrasts time Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Linear 291.207 1 291.207 11.564.002.285 Quadratic 4.800 1 4.800.486.491.016 Cubic 14.727 1 14.727 2.690.112.085 Linear 730.293 29 25.183 Quadratic 286.700 29 9.886 Cubic 158.773 29 5.475 Measure: MEASURE_1 Transformed Variable: Average Tests of Between-Subjects Effects Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Intercept 492544.533 1 492544.533 1143.164.000.975 Error 12494.967 29 430.861 T-TEST PAIRS = time1 time1 time1 time2 time2 time3 WITH time2 time3 time4 time3 time4 time4 (PAIRED) /CRITERIA = CI(.992) /MISSING = ANALYSIS.

T-Test Paired Samples Statistics Pair 1 Pair 2 Pair 3 Pair 4 Pair 5 Pair 6 Mean N Std. Deviation Std. Error Mean time1 65.80 30 9.227 1.685 time2 65.43 30 10.686 1.951 time1 65.80 30 9.227 1.685 time3 63.10 30 10.685 1.951 time1 65.80 30 9.227 1.685 time4 61.93 30 12.567 2.294 time2 65.43 30 10.686 1.951 time3 63.10 30 10.685 1.951 time2 65.43 30 10.686 1.951 time4 61.93 30 12.567 2.294 time3 63.10 30 10.685 1.951 time4 61.93 30 12.567 2.294 Paired Samples Correlations N Correlation Sig. Pair 1 time1 & time2 30.888.000 Pair 2 time1 & time3 30.879.000 Pair 3 time1 & time4 30.833.000 Pair 4 time2 & time3 30.949.000 Pair 5 time2 & time4 30.895.000 Pair 6 time3 & time4 30.943.000 Paired Samples Test Mean Paired Differences 99.2% Confidence Interval of the Difference Std. Error Std. Deviation Mean Lower Upper t df Sig. (2-tailed) Pair 1 time1 - time2.367 4.916.898-2.190 2.923.408 29.686 Pair 2 time1 - time3 2.700 5.100.931.048 5.352 2.900 29.007 Pair 3 time1 - time4 3.867 7.055 1.288.198 7.535 3.002 29.005 Pair 4 time2 - time3 2.333 3.397.620.567 4.100 3.762 29.001 Pair 5 time2 - time4 3.500 5.637 1.029.569 6.431 3.401 29.002 Pair 6 time3 - time4 1.167 4.348.794-1.094 3.428 1.470 29.152 Since repeated t-tests are conducted, a Bonferroni adjustment is needed..05 / 6 =.008. So, tests are conducted at an alpha level of.008.

SPANOVA GET FILE='/Users/richardbalkin/Desktop/CNEP 6372/SPANOVA data.sav'. EXAMINE VARIABLES=Pretest Posttest BY Exercisetype /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Input Missing Value Handling Notes Output Created 14-Jan-2010 13:10:07 Comments Data Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing Cases Used /Users/richardbalkin/Desktop/CNEP 6372/SPANOVA data.sav DataSet1 <none> <none> <none> User-defined missing values for dependent variables are treated as missing. 50 Statistics are based on cases with no missing values for any dependent variable or factor used.

Syntax EXAMINE VARIABLES=Pretest Posttest BY Exercisetype /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Resources Processor Time 0:00:02.704 Elapsed Time 0:00:03.000 [DataSet1] /Users/richardbalkin/Desktop/CNEP 6372/SPANOVA data.sav Exercise type Case Processing Summary Cases Exercis Valid Missing Total e type N Percent N Percent N Percent Pretest Posttest 1 25 100.0% 0.0% 25 100.0% 2 25 100.0% 0.0% 25 100.0% 1 25 100.0% 0.0% 25 100.0% 2 25 100.0% 0.0% 25 100.0%

Pretest Descriptives Exercise type Statistic Std. Error 1 2 Posttest 1 95% Confidence Interval for Mean 95% Confidence Interval for Mean Mean 2.34.067 Lower Bound 2.20 Upper Bound 2.48 5% Trimmed Mean 2.35 Median 2.45 Variance.112 Std. Deviation.335 Minimum 2 Maximum 3 Range 1 Interquartile Range 0 Skewness -.507.464 Kurtosis -.295.902 Mean 2.39.053 Lower Bound 2.28 Upper Bound 2.50 5% Trimmed Mean 2.40 Median 2.40 Variance.069 Std. Deviation.264 Minimum 2 Maximum 3 Range 1 Interquartile Range 0 Skewness -.596.464 Kurtosis -.824.902 Mean 2.76.021 95% Confidence Interval Lower Bound 2.71 for Mean Upper Bound 2.80

2 5% Trimmed Mean 2.76 Median 2.76 Variance.011 Std. Deviation.105 Minimum 2 Maximum 3 Range 0 Interquartile Range 0 Skewness -.163.464 Kurtosis 1.137.902 Mean 2.97.026 95% Confidence Interval Lower Bound 2.91 for Mean Upper Bound 3.02 5% Trimmed Mean 2.97 Median 2.96 Variance.017 Std. Deviation.129 Minimum 3 Maximum 3 Range 0 Interquartile Range 0 Skewness -.313.464 Kurtosis -.702.902 Tests of Normality Exercis Kolmogorov-Smirnov a Shapiro-Wilk e type Statistic df Sig. Statistic df Sig. Pretest Posttest 1.153 25.134.951 25.262 2.168 25.068.901 25.019 1.135 25.200 *.963 25.487 2.126 25.200 *.955 25.320

a. Lilliefors Significance Correction *. This is a lower bound of the true significance. Pretest Normal Q-Q Plots

Detrended Normal Q-Q Plots

Posttest Normal Q-Q Plots

Detrended Normal Q-Q Plots

GLM Pretest Posttest BY Exercisetype /WSFACTOR=time 2 Polynomial /METHOD=SSTYPE(3) /PLOT=PROFILE(time*Exercisetype) /PRINT=DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA=ALPHA(.05) /WSDESIGN=time /DESIGN=Exercisetype.

General Linear Model Input Missing Value Handling Notes Output Created 14-Jan-2010 13:11:49 Comments Data Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing Cases Used Syntax /Users/richardbalkin/Desktop/CNEP 6372/SPANOVA data.sav DataSet1 <none> <none> <none> User-defined missing values are treated as missing. Statistics are based on all cases with valid data for all variables in the model. GLM Pretest Posttest BY Exercisetype /WSFACTOR=time 2 Polynomial /METHOD=SSTYPE(3) 50 /PLOT=PROFILE(time*Exercisetype) /PRINT=DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA=ALPHA(.05) /WSDESIGN=time /DESIGN=Exercisetype. Resources Processor Time 0:00:00.232 Elapsed Time 0:00:01.000 [DataSet1] /Users/richardbalkin/Desktop/CNEP 6372/SPANOVA data.sav

Within-Subjects Factors Measure:MEASURE_1 time 1 Pretest 2 Posttest Dependent Variable Between-Subjects Factors N Exercise type 1 25 2 25 Pretest Posttest Descriptive Statistics Exercis e type Mean Std. Deviation N 1 2.34.335 25 2 2.39.264 25 Total 2.36.300 50 1 2.76.105 25 2 2.97.129 25 Total 2.86.158 50

Box's Test of Equality of Covariance Matrices a Box's M 3.573 F 1.137 df1 3 df2 414720.000 Sig..332 Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across groups. a. Design: Intercept + Exercisetype Within Subjects Design: time Multivariate Tests b Effect Value F Hypothesis df Error df Sig. time time * Exercisetype a. Exact statistic Partial Eta Squared Pillai's Trace.734 132.586 a 1.000 48.000.000.734 Wilks' Lambda.266 132.586 a 1.000 48.000.000.734 Hotelling's Trace 2.762 132.586 a 1.000 48.000.000.734 Roy's Largest Root 2.762 132.586 a 1.000 48.000.000.734 Pillai's Trace.067 3.433 a 1.000 48.000.070.067 Wilks' Lambda.933 3.433 a 1.000 48.000.070.067 Hotelling's Trace.072 3.433 a 1.000 48.000.070.067 Roy's Largest Root b. Design: Intercept + Exercisetype Within Subjects Design: time.072 3.433 a 1.000 48.000.070.067

Measure:MEASURE_1 Within Subjec ts Effect Mauchly's W a Mauchly's Test of Sphericity b Approx. Chi- Square df Sig. Epsilon a Greenhouse- Geisser Huynh-Feldt Lower-bound time 1.000.000 0. 1.000 1.000 1.000 Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an identity matrix. a. 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. b. Design: Intercept + Exercisetype Within Subjects Design: time

Measure:MEASURE_1 Source time time * Exercisetype Error(time) Sphericity Assumed Greenhouse- Geisser Tests of Within-Subjects Effects Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared 6.180 1 6.180 132.586.000.734 6.180 1.000 6.180 132.586.000.734 Huynh-Feldt 6.180 1.000 6.180 132.586.000.734 Lower-bound 6.180 1.000 6.180 132.586.000.734 Sphericity Assumed Greenhouse- Geisser.160 1.160 3.433.070.067.160 1.000.160 3.433.070.067 Huynh-Feldt.160 1.000.160 3.433.070.067 Lower-bound.160 1.000.160 3.433.070.067 Sphericity Assumed Greenhouse- Geisser 2.237 48.047 2.237 48.000.047 Huynh-Feldt 2.237 48.000.047 Lower-bound 2.237 48.000.047 Measure:MEASURE_1 Source time Tests of Within-Subjects Contrasts Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared time Linear 6.180 1 6.180 132.586.000.734 time * Exercisetype Linear.160 1.160 3.433.070.067 Error(time) Linear 2.237 48.047

Levene's Test of Equality of Error Variances a F df1 df2 Sig. Pretest 2.449 1 48.124 Posttest 2.360 1 48.131 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + Exercisetype Within Subjects Design: time Measure:MEASURE_1 Transformed Variable:Average Source Tests of Between-Subjects Effects Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Intercept 683.090 1 683.090 11743.727.000.996 Exercisetype.428 1.428 7.353.009.133 Error 2.792 48.058 Profile Plots

EXAMINE VARIABLES=statexam /PLOT BOXPLOT HISTOGRAM NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Multiple Regression Case Processing Summary Average percentage correct on statistics exams Cases Valid Missing Total N Percent N Percent N Percent 100 100.0% 0.0% 100 100.0% Descriptives Average percentage correct on statistics exams Statistic Std. Error Mean 60.11 1.979 95% Confidence Lower Bound 56.18 Interval for Mean Upper Bound 64.04 5% Trimmed Mean 60.21 Median 62.00 Variance 391.574 Std. Deviation 19.788 Minimum 23 Maximum 97 Range 74 Interquartile Range 33 Skewness -.101.241 Kurtosis -1.045.478 Average percentage correct on statistics exams a Lilliefors Significance Correction Tests of Normality Kolmogorov-Smirnov(a) Shapiro-Wilk Statistic df Sig. Statistic df Sig..079 100.127.967 100.013

Criterion variable should be normally distributed Average percentage correct on statistics exams REGRESSION /DESCRIPTIVES MEAN STDDEV CORR SIG N /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA COLLIN TOL ZPP /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT statexam /METHOD=ENTER mathtest engtest /SCATTERPLOT=(*ZRESID,*ZPRED ) /SAVE ZRESID.

on Descriptive Statistics Mean Std. Deviation N entage tistics 60.11 19.788 100 test score 460.60 77.366 100 de test 478.20 71.653 100 Correlations elation Average percentage correct on statistics exams Average percentage correct on statistics exams Math aptitude test score English aptitude test score 1.000.484.202 Math aptitude test score.484 1.000.121 English aptitude test score.202.121 1.000 Average percentage correct on statistics exams..000.022 Math aptitude test score.000..115 English aptitude test score.022.115. Average percentage correct on statistics exams 100 100 100 Math aptitude test score 100 100 100 English aptitude test score 100 100 100 r correlations and intercorrelations. When you divide the correlation of a predictor to the criterion by R you get the structure or that predictor.

ered/removed(b) riables ntered ish ude test e, Math ude test e(a) Variables Removed. Enter Method d variables entered. Variable: Average percentage correct on statistics exams Model Summary(b) R R Square Adjusted R Square Std. Error of the Estimate 505(a).255.240 17.251 Constant), English aptitude test score, Math aptitude test score Variable: Average percentage correct on statistics exams ariance accounted for in the model ANOVA(b) Sum of Squares df Mean Square F Sig. ression 9900.265 2 4950.133 16.634.000(a) dual 28865.525 97 297.583 l 38765.790 99 Constant), English aptitude test score, Math aptitude test score Variable: Average percentage correct on statistics exams of the model Coefficients(a) Unstandardized Coefficients Standardized Coefficients Correlations Collinear B Std. Error Beta t Sig. Zero-order Partial Part Tolerance nstant) -14.088 14.750 -.955.342 h aptitude test score.119.023.467 5.286.000.484.473.463.985 ish aptitude test e.040.024.146 1.650.102.202.165.145.985 Variable: Average percentage correct on statistics exams rdized beta coefficients are the amount of increase in the criterion for each change in the predict s show statistical significance of the beta weights. quare the part correlation you have the squared semi-partial correlation coefficient-the unique amo ontributed by a predictor variable. d tolerance show no multicollinearlity noted.

Collinearity Diagnostics(a) ension Eigenvalue Condition Index (Constant) Variance Proportions Math aptitude test score English aptitude test score 2.969 1.000.00.00.00.022 11.694.01.70.42.009 18.134.99.30.58 Variable: Average percentage correct on statistics exams Residuals Statistics(a) Minimum Maximum Mean Std. Deviation N ue 40.60 86.04 60.11 10.000 100-37.889 33.882.000 17.075 100 Value -1.951 2.593.000 1.000 100-2.196 1.964.000.990 100 Variable: Average percentage correct on statistics exams

have a constant variance. p between the criterion variable and each predictor variable should be linear. S=ZRE_1 XPLOT NPPLOT GROUP ICS DESCRIPTIVES AL 95 LISTWISE.

Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Residual 100 100.0% 0.0% 100 100.0% Descriptives Residual Statistic Std. Error Mean.0000000.09898475 95% Confidence Interval for Mean Lower Bound -.1964072 Upper Bound.1964072 5% Trimmed Mean.0100501 Median.0706431 Variance.980 Std. Deviation.98984745 Minimum -2.19638 Maximum 1.96412 Range 4.16051 Interquartile Range 1.73813 Skewness -.179.241 Kurtosis -.802.478 Tests of Normality Kolmogorov-Smirnov(a) Shapiro-Wilk Statistic df Sig. Statistic df Sig. Residual.093 100.033.977 100.079 nificance Correction diction should be normally distributed.

Standardized Residual

MANOVA with Discriminant Analysis Post hoc GET FILE='/Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 28/Lesson 28 Data File 1.sav'. EXAMINE VARIABLES=applicat recall BY group /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Input Missing Value Handling Notes Output Created 18-Feb-2010 10:42:17 Comments Data Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing Cases Used /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 28/Lesson 28 Data File 1.sav DataSet1 <none> <none> <none> User-defined missing values for dependent variables are treated as missing. 30 Statistics are based on cases with no missing values for any dependent variable or factor used.

Syntax EXAMINE VARIABLES=applicat recall BY group /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Resources Processor Time 0:00:03.488 Elapsed Time 0:00:03.000 [DataSet1] /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 28/Lesson 28 Data File 1.sav Study Strategy Groups Case Processing Summary Study Cases Strategy Valid Missing Total Groups N Percent N Percent N Percent Application Exam Recall Exam Think 10 100.0% 0.0% 10 100.0% Write 10 100.0% 0.0% 10 100.0% Talk 10 100.0% 0.0% 10 100.0% Think 10 100.0% 0.0% 10 100.0% Write 10 100.0% 0.0% 10 100.0% Talk 10 100.0% 0.0% 10 100.0% Descriptives Study Strategy Groups Statistic Std. Error

Application Exam Think Write Talk 95% Confidence Interval for Mean 95% Confidence Interval for Mean 95% Confidence Interval for Mean Mean 3.20.389 Lower Bound 2.32 Upper Bound 4.08 5% Trimmed Mean 3.22 Median 3.00 Variance 1.511 Std. Deviation 1.229 Minimum 1 Maximum 5 Range 4 Interquartile Range 2 Skewness -.018.687 Kurtosis.145 1.334 Mean 5.00.558 Lower Bound 3.74 Upper Bound 6.26 5% Trimmed Mean 5.06 Median 5.00 Variance 3.111 Std. Deviation 1.764 Minimum 2 Maximum 7 Range 5 Interquartile Range 3 Skewness -.304.687 Kurtosis -1.002 1.334 Mean 4.40.371 Lower Bound 3.56 Upper Bound 5.24 5% Trimmed Mean 4.39

Recall Exam Think Write Median 4.50 Variance 1.378 Std. Deviation 1.174 Minimum 3 Maximum 6 Range 3 Interquartile Range 2 Skewness.041.687 Kurtosis -1.457 1.334 Mean 3.30.213 95% Confidence Interval Lower Bound 2.82 for Mean Upper Bound 3.78 5% Trimmed Mean 3.33 Median 3.00 Variance.456 Std. Deviation.675 Minimum 2 Maximum 4 Range 2 Interquartile Range 1 Skewness -.434.687 Kurtosis -.283 1.334 Mean 5.80.327 95% Confidence Interval Lower Bound 5.06 for Mean Upper Bound 6.54 5% Trimmed Mean 5.72 Median 5.50 Variance 1.067 Std. Deviation 1.033 Minimum 5 Maximum 8

Talk Range 3 Interquartile Range 1 Skewness 1.241.687 Kurtosis.946 1.334 Mean 4.20.359 95% Confidence Interval Lower Bound 3.39 for Mean Upper Bound 5.01 5% Trimmed Mean 4.22 Median 4.00 Variance 1.289 Std. Deviation 1.135 Minimum 2 Maximum 6 Range 4 Interquartile Range 1 Skewness -.478.687 Kurtosis.552 1.334 Application Exam Recall Exam a. Lilliefors Significance Correction Tests of Normality Study Strategy Kolmogorov-Smirnov a Shapiro-Wilk Groups Statistic df Sig. Statistic df Sig. Think.265 10.046.899 10.212 Write.172 10.200 *.919 10.350 Talk.195 10.200 *.878 10.124 Think.272 10.035.802 10.015 Write.281 10.025.791 10.011 Talk.230 10.143.933 10.479 *. This is a lower bound of the true significance.

Application Exam Recall Exam

GLM recall applicat BY group /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PRINT=DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN= group.

General Linear Model Input Missing Value Handling Notes Output Created 18-Feb-2010 10:43:33 Comments Data Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing Cases Used Syntax /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 28/Lesson 28 Data File 1.sav DataSet1 <none> <none> <none> User-defined missing values are treated as missing. Statistics are based on all cases with valid data for all variables in the model. GLM recall applicat BY group /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PRINT=DESCRIPTIVE ETASQ HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN= group. 30 Resources Processor Time 0:00:00.006 Elapsed Time 0:00:00.000 [DataSet1] /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 28/Lesson 28 Data File 1.sav

Between-Subjects Factors Value Label N Study Strategy Groups 1 Think 10 2 Write 10 3 Talk 10 Recall Exam Application Exam Descriptive Statistics Study Strategy Groups Mean Std. Deviation N Think 3.30.675 10 Write 5.80 1.033 10 Talk 4.20 1.135 10 Total 4.43 1.406 30 Think 3.20 1.229 10 Write 5.00 1.764 10 Talk 4.40 1.174 10 Total 4.20 1.562 30 Box's Test of Equality of Covariance Matrices a Box's M 6.980 F 1.039 df1 6 df2 18168.923 Sig..398

Tests the null hypothesis that the observed covariance matrices of the dependent variables are equal across groups. a. Design: Intercept + group Multivariate Tests c Effect Value F Hypothesis df Error df Sig. Intercept group a. Exact statistic Partial Eta Squared Pillai's Trace.962 326.035 a 2.000 26.000.000.962 Wilks' Lambda.038 326.035 a 2.000 26.000.000.962 Hotelling's Trace 25.080 326.035 a 2.000 26.000.000.962 Roy's Largest Root 25.080 326.035 a 2.000 26.000.000.962 Pillai's Trace.602 5.811 4.000 54.000.001.301 Wilks' Lambda.421 7.028 a 4.000 52.000.000.351 Hotelling's Trace 1.318 8.240 4.000 50.000.000.397 Roy's Largest Root 1.275 17.215 b 2.000 27.000.000.560 b. The statistic is an upper bound on F that yields a lower bound on the significance level. c. Design: Intercept + group Levene's Test of Equality of Error Variances a F df1 df2 Sig. Recall Exam.711 2 27.500 Application Exam 1.202 2 27.316 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + group

Source Corrected Model Intercept group Error Total Corrected Total Dependent Variable Tests of Between-Subjects Effects Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared Recall Exam 32.067 a 2 16.033 17.111.000.559 Application Exam 16.800 b 2 8.400 4.200.026.237 Recall Exam 589.633 1 589.633 629.253.000.959 Application Exam 529.200 1 529.200 264.600.000.907 Recall Exam 32.067 2 16.033 17.111.000.559 Application Exam 16.800 2 8.400 4.200.026.237 Recall Exam 25.300 27.937 Application Exam 54.000 27 2.000 Recall Exam 647.000 30 Application Exam 600.000 30 Recall Exam 57.367 29 Application Exam a. R Squared =.559 (Adjusted R Squared =.526) b. R Squared =.237 (Adjusted R Squared =.181) 70.800 29 DISCRIMINANT /GROUPS=group(1 3) /VARIABLES=recall applicat /ANALYSIS ALL /PRIORS EQUAL /PLOT=COMBINED /CLASSIFY=NONMISSING POOLED. Discriminant

Input Missing Value Handling Notes Output Created 18-Feb-2010 10:50:39 Comments Data Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing Cases Used Syntax /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 28/Lesson 28 Data File 1.sav DataSet1 <none> <none> <none> User-defined missing values are treated as missing in the analysis phase. 30 In the analysis phase, cases with no user- or system-missing values for any predictor variable are used. Cases with user-, system-missing, or out-of-range values for the grouping variable are always excluded. DISCRIMINANT /GROUPS=group(1 3) /VARIABLES=recall applicat /ANALYSIS ALL /PRIORS EQUAL /PLOT=COMBINED /CLASSIFY=NONMISSING POOLED. Resources Processor Time 0:00:00.231 Elapsed Time 0:00:01.000 [DataSet1] /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 28/Lesson 28 Data File 1.sav

Analysis Case Processing Summary Unweighted Cases N Percent Excluded Valid 30 100.0 Missing or out-of-range group codes At least one missing discriminating variable Both missing or out-ofrange group codes and at least one missing discriminating variable 0.0 0.0 0.0 Total 0.0 Total 30 100.0 Group Statistics Valid N (listwise) Study Strategy Groups Unweighted Weighted Think Recall Exam 10 10.000 Application Exam 10 10.000 Write Talk Total Recall Exam 10 10.000 Application Exam 10 10.000 Recall Exam 10 10.000 Application Exam 10 10.000 Recall Exam 30 30.000 Application Exam 30 30.000 Analysis 1 Summary of Canonical Discriminant Functions

Eigenvalues Functio n Eigenvalue % of Variance Cumulative % Canonical Correlation 1 1.275 a 96.7 96.7.749 2.043 a 3.3 100.0.203 a. First 2 canonical discriminant functions were used in the analysis. Wilks' Lambda Test of Function(s) Wilks' Lambda Chi-square df Sig. 1 through 2.421 22.904 4.000 2.959 1.120 1.290 Standardized Canonical Discriminant Function Coefficients Function 1 2 Recall Exam.963 -.508 Application Exam.086 1.085 Structure Matrix Function 1 2 Recall Exam.997 * -.079 Application Exam.466.885 *

Pooled within-groups correlations between discriminating variables and standardized canonical discriminant functions Variables ordered by absolute size of correlation within function. *. Largest absolute correlation between each variable and any discriminant function Functions at Group Centroids Study Function Strategy Groups 1 2 Think -1.188 -.173 Write 1.408 -.103 Talk -.220.276 Unstandardized canonical discriminant functions evaluated at group means Classification Statistics Excluded Classification Processing Summary Processed 30 Missing or out-of-range group codes At least one missing discriminating variable Used in Output 30 0 0 Prior Probabilities for Groups

Study Cases Used in Analysis Strategy Groups Prior Unweighted Weighted Think.333 10 10.000 Write.333 10 10.000 Talk.333 10 10.000 Total 1.000 30 30.000

Canonical Correlation manova coping followup with TSR_Beh TSR_Emo /discrim all alpha(1) /print=sig (eigen dim). Manova Input Notes Output Created 22-Apr-2010 11:49:38 Comments Data Active Dataset Filter Weight Split File N of Rows in Working Data File Syntax /Volumes/Cruzer/Family Journal Article/GASS Family Journal Data.sav DataSet5 <none> <none> <none> manova coping followup with TSR_Beh TSR_Emo /discrim all alpha(1) /print=sig (eigen dim). 125 Resources Processor Time 0:00:00.005 Elapsed Time 0:00:00.000 [DataSet5] /Volumes/Cruzer/Family Journal Article/GASS Family Journal Data.sav - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - The default error term in MANOVA has been changed from WITHIN CELLS to

WITHIN+RESIDUAL. Note that these are the same for all full factorial designs. * * * * * * * * * * * * * * * * * A n a l y s i s o f V a r i a n c e * * * * * * * * * * * * * * * * * 120 cases accepted. 0 cases rejected because of out-of-range factor values. 5 cases rejected because of missing data. 1 non-empty cell. 1 design will be processed. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - * * * * * * * * * * * * * * * * * A n a l y s i s o f V a r i a n c e -- Design 1 * * * * * * * * * * * * * * * * * EFFECT.. WITHIN CELLS Regression Multivariate Tests of Significance (S = 2, M = -1/2, N = 57 ) Test Name Value Approx. F Hypoth. DF Error DF Sig. of F Pillais.11225 3.47841 4.00 234.00.009 Hotellings.12571 3.61414 4.00 230.00.007 Wilks.88806 3.54704 4.00 232.00.008 Roys.10947 Note.. F statistic for WILKS' Lambda is exact. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Eigenvalues and Canonical Correlations Root No. Eigenvalue Pct. Cum. Pct. Canon Cor. Sq. Cor 1.12292 97.78255 97.78255.33086.10947 2.00279 2.21745 100.00000.05272.00278 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Dimension Reduction Analysis Roots Wilks L. F Hypoth. DF Error DF Sig. of F 1 TO 2.88806 3.54704 4.00 232.00.008 2 TO 2.99722.32614 1.00 117.00.569 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

EFFECT.. WITHIN CELLS Regression (Cont.) Univariate F-tests with (2,117) D. F. Variable Sq. Mul. R Adj. R-sq. Hypoth. MS Error MS F Sig. of F coping.10941.09419 901.32243 125.40731 7.18716.001 followup.04460.02827 49.05777 17.96304 2.73104.069 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Raw canonical coefficients for DEPENDENT variables Function No. Variable 1 2 coping.08354 -.06708 followup.00641.29314 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Standardized canonical coefficients for DEPENDENT variables Function No. Variable 1 2 coping.98298 -.78931 followup.02756 1.26036 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Correlations between DEPENDENT and canonical variables Function No. Variable 1 2 coping.99976 -.02186 followup.62611.77974 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Variance in dependent variables explained by canonical variables CAN. VAR. Pct Var DEP Cum Pct DEP Pct Var COV Cum Pct COV 1 69.57676 69.57676 7.61629 7.61629 2 30.42324 100.00000.08457 7.70086 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Raw canonical coefficients for COVARIATES

Function No. COVARIATE 1 2 TSR_Beh -1.44177.96302 TSR_EMO.99511 1.75394 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Standardized canonical coefficients for COVARIATES CAN. VAR. COVARIATE 1 2 TSR_Beh -.83377.55691 TSR_EMO.49478.87208 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Correlations between COVARIATES and canonical variables CAN. VAR. Covariate 1 2 TSR_Beh -.86976.49347 TSR_EMO.55543.83156 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Variance in covariates explained by canonical variables CAN. VAR. Pct Var DEP Cum Pct DEP Pct Var COV Cum Pct COV 1 5.82904 5.82904 53.24979 53.24979 2.12996 5.95900 46.75021 100.00000 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Regression analysis for WITHIN CELLS error term --- Individual Univariate.9500 confidence intervals Dependent variable.. coping COVARIATE B Beta Std. Err. t-value Sig. of t Lower - 95% CL- Upper TSR_Beh -5.6245137505 -.2764344036 1.77988-3.16006.002-9.14947-2.09956 TSR_EMO 3.8492447377.1626560988 2.07015 1.85940.065 -.25058 7.94907 Dependent variable.. followup

COVARIATE B Beta Std. Err. t-value Sig. of t Lower - 95% CL- Upper TSR_Beh -1.1138967394 -.1498228077.67363-1.65358.101-2.44798.22018 TSR_EMO 1.1963149939.1383458903.78349 1.52691.129 -.35534 2.74797 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - * * * * * * * * * * * * * * * * * A n a l y s i s o f V a r i a n c e -- Design 1 * * * * * * * * * * * * * * * * * EFFECT.. CONSTANT Multivariate Tests of Significance (S = 1, M = 0, N = 57 ) Test Name Value Exact F Hypoth. DF Error DF Sig. of F Pillais.44315 46.15760 2.00 116.00.000 Hotellings.79582 46.15760 2.00 116.00.000 Wilks.55685 46.15760 2.00 116.00.000 Roys.44315 Note.. F statistics are exact. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Eigenvalues and Canonical Correlations Root No. Eigenvalue Pct. Cum. Pct. Canon Cor. 1.79582 100.00000 100.00000.66570 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - EFFECT.. CONSTANT (Cont.) Univariate F-tests with (1,117) D. F. Variable Hypoth. SS Error SS Hypoth. MS Error MS F Sig. of F coping 9744.20349 14672.65513 9744.20349 125.40731 77.70044.000 followup 1251.16804 2101.67614 1251.16804 17.96304 69.65234.000 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - EFFECT.. CONSTANT (Cont.)

Raw discriminant function coefficients Function No. Variable 1 coping.05531 followup.11845 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Standardized discriminant function coefficients Function No. Variable 1 coping.61938 followup.50201 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Estimates of effects for canonical variables Canonical Variable Parameter 1 1 6.39925 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Correlations between DEPENDENT and canonical variables Canonical Variable Variable 1 coping.91351 followup.86490 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

ANCOVA GET FILE='/Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 27/Lesson 27 Data File 1.sav'. EXAMINE VARIABLES=days predays BY group /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Explore Input Missing Value Handling Notes Output Created 25-Feb-2010 15:26:34 Comments Data Active Dataset Filter Weight Split File N of Rows in Working Data File Definition of Missing Cases Used /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 27/Lesson 27 Data File 1.sav DataSet1 <none> <none> <none> User-defined missing values for dependent variables are treated as missing. 30 Statistics are based on cases with no missing values for any dependent variable or factor used.

Syntax EXAMINE VARIABLES=days predays BY group /PLOT BOXPLOT NPPLOT /COMPARE GROUP /STATISTICS DESCRIPTIVES /CINTERVAL 95 /MISSING LISTWISE /NOTOTAL. Resources Processor Time 0:00:03.469 Elapsed Time 0:00:04.000 [DataSet1] /Users/richardbalkin/Desktop/CNEP 6370/GreenSalkind/Lesson 27/Lesson 27 Data File 1.sav Vitamin C Treatment Case Processing Summary Cases Valid Missing Total Vitamin C Treatment N Percent N Percent N Percent Days with Colds: Post Placebo 10 100.0% 0.0% 10 100.0% Low Vitamin C Dose 10 100.0% 0.0% 10 100.0% High Vitamin C Dose 10 100.0% 0.0% 10 100.0% Days with Colds: Prior Placebo 10 100.0% 0.0% 10 100.0% Low Vitamin C Dose 10 100.0% 0.0% 10 100.0% High Vitamin C Dose 10 100.0% 0.0% 10 100.0%

Days with Colds: Post Vitamin C Treatment Placebo Low Vitamin C Dose Descriptives 95% Confidence Interval for Mean 95% Confidence Interval for Mean Statistic Std. Error Mean 11.60 1.694 Lower Bound 7.77 Upper Bound 15.43 5% Trimmed Mean 11.78 Median 12.50 Variance 28.711 Std. Deviation 5.358 Minimum 0 Maximum 20 Range 20 Interquartile Range Skewness -.850.687 Kurtosis 1.912 1.334 Mean 8.40 1.213 Lower Bound 5.66 Upper Bound 11.14 5% Trimmed Mean 8.61 Median 9.50 Variance 14.711 Std. Deviation 3.836 Minimum 0 Maximum 13 Range 13 Interquartile Range Skewness -1.284.687 Kurtosis 1.701 1.334 High Vitamin C Mean 6.40 1.097 6 4

Days with Colds: Prior Placebo Low Vitamin C Dose 95% Confidence Interval for Mean Lower Bound 3.92 Upper Bound 8.88 5% Trimmed Mean 6.39 Median 6.50 Variance 12.044 Std. Deviation 3.471 Minimum 0 Maximum 13 Range 13 Interquartile Range Skewness.018.687 Kurtosis 1.325 1.334 Mean 8.10 1.871 95% Confidence Lower Bound 3.87 Interval for Mean Upper Bound 12.33 5% Trimmed Mean 7.94 Median 8.00 Variance 34.989 Std. Deviation 5.915 Minimum 0 Maximum 19 Range 19 Interquartile Range Skewness.251.687 Kurtosis -.116 1.334 Mean 10.50 1.851 95% Confidence Lower Bound 6.31 Interval for Mean Upper Bound 14.69 5% Trimmed Mean 10.61 Median 12.00 4 9

High Vitamin C Dose Variance 34.278 Std. Deviation 5.855 Minimum 0 Maximum 19 Range 19 Interquartile Range 10 Skewness -.438.687 Kurtosis -.537 1.334 Mean 8.40 1.614 95% Confidence Lower Bound 4.75 Interval for Mean Upper Bound 12.05 5% Trimmed Mean 8.50 Median 9.50 Variance 26.044 Std. Deviation 5.103 Minimum 0 Maximum 15 Range 15 Interquartile Range Skewness -.779.687 Kurtosis -.299 1.334 8 Tests of Normality Kolmogorov-Smirnov a Shapiro-Wilk Vitamin C Treatment Statistic df Sig. Statistic df Sig. Days with Colds: Post Placebo.163 10.200 *.941 10.566 Low Vitamin C Dose.258 10.057.882 10.136 High Vitamin C Dose.154 10.200 *.967 10.861 Days with Colds: Prior Placebo.139 10.200 *.954 10.712

Low Vitamin C Dose.201 10.200 *.957 10.755 High Vitamin C Dose.169 10.200 *.907 10.258 a. Lilliefors Significance Correction *. This is a lower bound of the true significance. Days with Colds: Post

Days with Colds: Prior

UNIANOVA days BY group WITH predays /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /CRITERIA=ALPHA(0.05) /DESIGN=group predays group*predays.