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 (Tukey's HSD, Tukey-Kramer, Games-Howell) * 7) ANOVA substitute tests (Welch's ANOVA, Brown-Forsythe F test) * 8) Variance comparison tests (F test, Levene's 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 means and of population proportions (includes calculation of min sample size and verification of ALL required assumptions) * 13) Combinations and Permutations (many different examples of each) * 14) Correlations - Pearson and Spearman (includes calculation of r Critical and p value of calculated r) * 15) Covariance * 16) Automated histograms, sorting, and charting created with formulas that automatically re-calculate when data changes * 17) Central Limit Theorem demonstrated in Excel * 18) Lots of problems solved in Excel using the following distributions: Normal, t, Binomial, Negative Binomial, F, Chi-Square, Poisson, Exponential, Uniform, Geometric, Beta, Gamma, Hypergeometric, and Multinomial * 19) Instructions to create user-interactive PDF and CDF graphs in Excel for the following distributions: Normal, t, Binomial, Chi-Square, Poisson, Exponential, Uniform, Beta, Gamma, and Hypergeometric * This book is complete and thorough enough for the professional statistician but simple and clear enough for the new statistics student. The reader of this book will become an Excel Statistical Master