Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).
May not be copied, scanned, or duplicated, in whole or in part.
Source: Percentage points calculated using Minitab software.Ĭopyright 2020 Cengage Learning.
Compass sans medium excel 2011 download how to#
Achieving the Objective of Inferential Statistics: The Necessary StepsĬhapter 2: Describing Data with Numerical MeasuresĢ.3 Understanding and Interpreting the Standard Deviationģ.1 Describing Bivariate Categorical Dataģ.2 Describing Bivariate Quantitative DataĬase Study: Are Your Clothes Really Clean?Ĥ.2 Calculating Probabilities Using Simple EventsĬase Study: Probability and Decision Making in the CongoĬhapter 5: Discrete Probability Distributionsĥ.1 Discrete Random Variables and Their Probability Distributionsĥ.2 The Binomial Probability Distributionĥ.4 The Hypergeometric Probability DistributionĬase Study: A Mystery: Cancers Near a ReactorĬhapter 6: The Normal Probability DistributionĦ.1 Probability Distributions for Continuous Random VariablesĦ.3 The Normal Approximation to the Binomial Probability DistributionĬase Study: "Are You Going to Curve the Grades?"ħ.1 Sampling Plans and Experimental Designsħ.2 Statistics and Sampling Distributionsħ.3 The Central Limit Theorem and the Sample Meanħ.5 The Sampling Distribution of the Sample Proportionħ.6 A Sampling Application: Statistical Process Control (Optional)Ĭase Study: Sampling the Roulette at Monte CarloĨ.1 Where We've Been and Where We're GoingĨ.4 Estimating the Difference between Two Population MeansĨ.5 Estimating the Difference between Two Binomial ProportionsĬase Study: How Reliable Is That Poll? CBS News: How and Where America EatsĬhapter 9: Large-Sample Tests of Hypothesesĩ.2 A Large-Sample Test about a Population Meanĩ.3 A Large-Sample Test of Hypothesis for the Difference between Two Population Meansĩ.4 A Large-Sample Test of Hypothesis for a Binomial Proportionĩ.5 A Large-Sample Test of Hypothesis for the Difference between Two Binomial Proportionsĩ.6 Concluding Comments on Testing Hypothesesġ0.2 Small-Sample Inferences Concerning a Population Meanġ0.3 Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samplesġ0.4 Small-Sample Inferences for the Difference between Two Means: A Paired-Difference Testġ0.5 Inferences Concerning a Population Varianceġ0.7 Revisiting the Small-Sample AssumptionsĬase Study: School Accountability-Are We Doing Better?ġ1.2 The Completely Randomized Design: A One-Way Classificationġ1.4 The Randomized Block Design: A Two-Way Classificationġ1.5 The a x b Factorial Experiment: A Two-Way Classificationġ1.6 Revisiting the Analysis of Variance AssumptionsĬase Study: How to Save Money on Groceries!Ĭhapter 12: Simple Linear Regression and Correlationġ2.2 An Analysis of Variance for Linear Regressionġ2.3 Testing the Usefulness of the Linear Regression Modelġ2.4 Diagnostic Tools for Checking the Regression Assumptionsġ2.5 Estimation and Prediction Using the Fitted LineĬase Study: Is Your Car "Made in the U.S.A."?Ĭhapter 13: Multiple Linear Regression Analysisġ3.4 Using Quantitative and Qualitative Predictor Variables in a Regression Modelġ3.5 Testing Sets of Regression Coefficientsġ3.6 Other Topics in Multiple Linear Regressionġ3.7 Steps to Follow When Building a Multiple Regression ModelĬase Study: "Made in the U.S.A."-Another Lookġ4.1 The Multinomial Experiment and the Chi-Square Statisticġ4.2 Testing Specified Cell Probabilities: The Goodness-of-Fit Testġ4.3 Contingency Tables: A Two-Way Classificationġ4.4 Comparing Several Multinomial Populations: A Two-Way Classification with Fixed Row or Column Totalsġ4.5 Other Topics in Categorical Data AnalysisĬase Study: Who Is the Primary Breadwinner in Your Family?ġ5.1 The Wilcoxon Rank Sum Test: Independent Random Samplesġ5.2 The Sign Test for a Paired Experimentġ5.4 The Wilcoxon Signed-Rank Test for a Paired Experimentġ5.5 The Kruskal-Wallis H-Test for Completely Randomized Designsġ5.6 The Friedman Fr-Test for Randomized Block DesignsĬritical Values of t, pages 692–963 t.100
0 kommentar(er)
