Introduction Chapter 1 About Variables and Values Variables and Values Recording Data in Lists Scales of Measurement Category Scales Numeric Scales Telling an Interval Value from a Text Value Charting Numeric Variables in Excel Charting Two Variables Understanding Frequency Distributions Using Frequency Distributions Building a Frequency Distribution from a Sample Building Simulated Frequency Distributions Chapter 2 How Values Cluster Together Calculating the Mean Understanding Functions, Arguments, and Results Understanding Formulas, Results, and Formats Minimizing the Spread Calculating the Median Choosing to Use the Median Calculating the Mode Getting the Mode of Categories with a Formula From Central Tendency to Variability Chapter 3 Variability: How Values Disperse Measuring Variability with the Range The Concept of a Standard Deviation Arranging for a Standard Thinking in Terms of Standard Deviations Calculating the Standard Deviation and Variance Squaring the Deviations Population Parameters and Sample Statistics Dividing by N - 1 Bias in the Estimate Degrees of Freedom Excel''s Variability Functions Standard Deviation Functions Variance Functions Chapter 4 How Variables Move Jointly: Correlation Understanding Correlation The Correlation, Calculated Using the CORREL() Function Using the Analysis Tools Using the Correlation Tool Correlation Isn''t Causation Using Correlation Removing the Effects of the Scale Using the Excel Function Getting the Predicted Values Getting the Regression Formula Using TREND() for Multiple Regression Combining the Predictors Understanding "Best Combination" Understanding Shared Variance A Technical Note: Matrix Algebra and Multiple Regression in Excel Moving on to Statistical Inference Chapter 5 How Variables Classify Jointly: Contingency Tables Understanding One-Way Pivot Tables Running the Statistical Test Making Assumptions Random Selection Independent Selections The Binomial Distribution Formula Using the BINOM.INV() Function Understanding Two-Way Pivot Tables Probabilities and Independent Events Testing the Independence of Classifications The Yule Simpson Effect Summarizing the Chi-Square Functions Chapter 6 Telling the Truth with Statistics Problems with Excel''s Documentation A Context for Inferential Statistics Understanding Internal Validity The F-Test Two-Sample for Variances Why Run the Test? Chapter 7 Using Excel with the Normal Distribution About the Normal Distribution Characteristics of the Normal Distribution The Unit Normal Distribution Excel Functions for the Normal Distribution The NORM.DIST() Function The NORM.INV() Function Confidence Intervals and the Normal Distribution The Meaning of a Confidence Interval Constructing a Confidence Interval Excel Worksheet Functions That Calculate Confidence Intervals Using CONFIDENCE.NORM() and CONFIDENCE() Using CONFIDENCE.T() Using the Data Analysis Add-in for Confidence Intervals Confidence Intervals and Hypothesis Testing The Central Limit Theorem Making Things Easier Making Things Better Chapter 8 Testing Differences Between Means: The Basics Testing Means: The Rationale Using a z-Test Using the Standard Error of the Mean Creating the Charts Using the t-Test Instead of the z-Test Defining the Decision Rule Understanding Statistical Power Chapter 9 Testing Differences Between Means: Further Issues Using Excel''s T.DIST() and T.INV() Functions to Test Hypotheses Making Directional and Nondirectional Hypotheses Using Hypotheses to Guide Excel''s t-Distribution Functions Completing the Picture with T.

DIST() Using the T.TEST() Function Degrees of Freedom in Excel Functions Equal and Unequal Group Sizes The T.TEST() Syntax Using the Data Analysis Add-in t-Tests Group Variances in t-Tests Visualizing Statistical Power When to Avoid t-Tests Chapter 10 Testing Differences Between Means: The Analysis of Variance Why Not t-Tests? The Logic of ANOVA Partitioning the Scores Comparing Variances The F Test Using Excel''s F Worksheet Functions Using F.DIST() and F.DIST.RT() Using F.INV() and FINV() The F Distribution Unequal Group Sizes Multiple Comparison Procedures The Scheffè Procedure Planned Orthogonal Contrasts Chapter 11 Analysis of Variance: Further Issues Factorial ANOVA Other Rationales for Multiple Factors Using the Two-Factor ANOVA Tool The Meaning of Interaction The Statistical Significance of an Interaction Calculating the Interaction Effect The Problem of Unequal Group Sizes Repeated Measures: The Two Factor Without Replication Tool Excel''s Functions and Tools: Limitations and Solutions Power of the F Test Mixed Models Chapter 12 Multiple Regression Analysis and Effect Coding: The Basics Multiple Regression and ANOVA Using Effect Coding Effect Coding: General Principles Other Types of Coding Multiple Regression and Proportions of Variance Understanding the Segue from ANOVA to Regression The Meaning of Effect Coding Assigning Effect Codes in Excel Using Excel''s Regression Tool with Unequal Group Sizes Effect Coding, Regression, and Factorial Designs in Excel Exerting Statistical Control with Semipartial Correlations Using a Squared Semipartial to get the Correct Sum of Squares Using TREND() to Replace Squared Semipartial Correlations Working with the Residuals Using Excel''s Absolute and Relative Addressing to Extend the Semipartials Chapter 13 Multiple Regression Analysis: Further Issues Solving Unbalanced Factorial Designs Using Multiple Regression Variables Are Uncorrelated in a Balanced Design Variables Are Correlated in an Unbalanced Design Order of Entry Is Irrelevant in the Balanced Design Order Entry Is Important in the Unbalanced Design About Fluctuating Proportions of Variance Experimental Designs, Observational Studies, and Correlation Using All the LINEST() Statistics Using the Regression Coefficients Using the Standard Errors Dealing with the Intercept Understanding LINEST()''s Third, Fourth, and Fifth Rows Managing Unequal Group Sizes in a True Experiment Managing Unequal Group Sizes in Observational Research Chapter 14 Analysis of Covariance: The Basics The Purposes of ANCOVA Greater Power Bias Reduction Using ANCOVA to Increase Statistical Power ANOVA Finds No Significant Mean Difference Adding a Covariate to the Analysis Testing for a Common Regression Line Removing Bias: A Different Outcome Chapter 15 Analysis of Covariance: Further Issues Adjusting Means with LINEST() and Effect Coding Effect Coding and Adjusted Group Means Multiple Comparisons Following ANCOVA Using the Scheffè Method Using Planned Contrasts The Analysis of Multiple Covariance The Decision to Use Multiple Covariates Two Covariates: An Example 9780789747204 TOC 4/6/2011.