Practical and Clear Graduate Statistics in Excel - The Excel Statistical Master
Cód:
491_9781937159139
Complete and practical yet easy-to-understand graduate-level statistics instruction with ALL of the problems and examples worked out in the accompanying Excel workbooks. Thoroughly covers all topics of an intense graduate statistics course using nothing but step-by-step, simple explanations. Some of the major topics covered with easy-to-follow explanations and fully described and demonstrated in detail in Excel include: 1) ALL types of t-Tests (1-sample, 2-sample pooled and unpooled, and paired) and z tests including verification of ALL required assumptions * 2) Single-variable and multiple regression (includes verification of ALL required assumptions and ALL underlying formulas used to produce Excel regression output) * 3) Logistic regression (Logit and P(X), MLL, Max Log-Likelihood Function, R Square (Cox and Snell and Nagelkerke), variable significance with Likelihood Ratio, Classification Table, Hosmer-Lemeshow) * 4) Normality Tests (Kolmogorov-Smirnov, Anderson-Darlington, Shapiro-Wilk, Automated Histograms) * 5) Single-factor and two-factor ANOVA with and without replication including verification of ALL required assumptions and ALL underlying formulas used to produce Excel ANOVA output * 6) Post-Hoc tests for ANOVA (Tukeys HSD, Tukey-Kramer, Games-Howell) * 7) ANOVA substitute tests (Welchs ANOVA, Brown-Forsythe F test) * 8) Variance comparison tests (F test, Levenes test, Brown-Forsythe test) *9) Effect size tests (Eta square, RMSSE, Omega square) *10) Detailed description of calculating test power using the online utility G*Power for all types of tests) *11) Nonparametric tests (Mann-Whitney U test alternative for 2-sample t-Tests, Wilcoxon Signed-Rank test alternative for 1-sample and paired t-Tests, Kruskal-Wallis test alternative for 1-way ANOVA, Scheirer-Ray-Hare test alternative for 2-way ANOVA, Sign Test) *11) Chi-Square tests (Goodness-of-Fit, Independence tests, and population variance tests) *12) Confidence intervals of population
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