Chapter Twenty-Four - Additional Resources
Reading
Chapter 24.1 - Examples of Reporting Statistics Used Chapter 24.2 - A Probability Test For Use With Likert-type Scales Chapter 24.3 - Fisher Exact Test/Binomial Test Chapter 24.4 - The Phi coefficient Chapter 24.5 - XTSignificance of the difference between two proportions Chapter 24.6 - The k-sample slippage test (Conover, 1971)
Boxes for Chapter Twenty-Four
24.1 Frequencies and percentages for a course evaluation 24.2 Crosstabulation by totals 24.3 Crosstabulation by row totals 24.4 Rating scale of agreement and disagreement 24.5 Satisfaction with a course 24.6 Combined categories of rating scales 24.7 Representing combined categories of rating scales 24.8 How well learners are cared for, guided and supported 24.9 Staff voluntarily taking on coordination roles 24.10 Distribution of test scores 24.11 A line graph of test scores 24.12 Distribution around a mean with an outlier 24.13 A platykurtic distribution of scores 24.14 A leptokurtic distribution of scores 24.15 Type one and Type II errors 24.16 Mean and standard deviation in an effect size 24.17 The Levene test for equality of variances 24.18 Mean and standard deviation in a paired sample test 24.19 Difference test for a paired sample 24.20 Effect size in analysis of variance 24.21 A 2 x 3 contingency table for chi-square 24.22 A 2 x 5 contingency table for chi-square 24.23 Common measures of relationship 24.24 Percentage of pubic library members by their social class origin 24.25 Correlation scatterplots 24.26 A Pearson product moment correlation 24.27 A line diagram to indicate curvilinearity 24.28 Visualization of correlation of 0.65 between reading grade and arithmetic grade 24.29 a scatterplot with the regression line 24.30 A scatterplot with grid lines and regression line 24.31 A summary of the R, R square and adjusted R square in regression analysis 24.32 Significance level in regression analysis 24.33 The beta coefficient in a regression analysis 24.34 A summary of the R, R square and adjusted R square in multiple regression analysis 24.35 Significance level in multiple regression analysis 24.36 The beta coefficients in a multiple regression analysis 24.37 Means and standard deviations for a t-test 24.38 The Levene test for equality of variances in a t-test 24.39 A t-test for leaders and teachers 24.40 The Levene test for equality of variances between leaders and teachers 24.41 Means and standard deviations in a paired samples t-test 24.42 The paired samples t-test 24.43 Descriptive statistics for analysis of variance 24.44 SPSS output for one-way analysis of variance 24.45 The Tukey test 24.46 Homogeneous groupings in the Tukey test 24.47 Means and standard deviations in a two-way analysis of variance 24.48 The Levene test of equality of variances in a two-way analysis of variance 24.49 Between-subject effects in two-way analysis of variance 24.50 Graphic plots of two sets of scores on a dependent variable 24.51 A cross-tabulation for a Mann-Whitney U test 24.52 SPSS output on rankings for the Mann-Whitney U test 24.53 The Mann-Whitney U value and significance level in SPSS 24.54 Frequencies and percentages of variable one in a Wilcoxon test 24.55 Frequencies and percentages of variable two in a Wilcoxon test 24.56 Ranks and sums of ranks in a Wilcoxon test 24.57 Significance level in a Wilcoxon test 24.58 Cross-tabulation for the Kruskal-Wallis test 24.59 Rankings for the Kruskal-Wallis test 24.60 Significance levels in a Kruskal-Wallis test 24.61 Frequencies for variable one in the Friedman test 24.62 Frequencies for variable two in the Friedman test 24.63 Frequencies for variable three in the Friedman test 24.64 Rankings for the Friedman test 24.65 Significance level in the Friedman test
Powerpoint Presentations
Chapter 24.1 Chapter 24.2 Chapter 24.3 Chapter 24.4 Chapter 24.5 Chapter 24.6 Chapter 24.7 Chapter 24.8 Chapter 24.9 Chapter 24.10 Chapter 24.11 Chapter 24.12 Chapter 24.13 Chapter 24.14 Chapter 24.15 Chapter 24.16 Chapter 24.17 Chapter 24.18 Chapter 24.19 Chapter 24.20
