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Author:   Laelie Snook
Publisher:   Kendall/Hunt Publishing Co ,U.S.
Imprint:   Kendall/Hunt Publishing Co ,U.S.
ISBN:  

9781792405600

ISBN 10:   179240560
Pages:   277
Publication Date:   30 August 2019
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   Temporarily unavailable  
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Table of Contents

Chapter One: Introduction 1.1 Overview of Course (Basic Concepts) Population Sample Random Sample Internal and External Validity 1.2 Why We Sample Sampling to Determine ? Sampling to Determine p Excel Excitement Summary Exercises Chapter Two: Organizing and Analyzing Data 2.1 Graphical Representations Histogram Population Histograms Frequency Polygon Circle Graph 2.2 Measures of Central Tendency (Ungrouped Data) Arithmetic Mean Median Mode Comparison of the Mean, Median, and Mode 2.3 Measures of Dispersion or Spread (Ungrouped Data) Range Standard Deviation 2.4 Estimating Population Characteristics 2.5 Measures of Central Tendency and Dispersion/Spread (Grouped Data) Mean Standard Deviation Modal Class 2.6 z Scores and the Use of the Standard Deviation Two Important Findings 2.7 Additional Descriptive Topics Pictogram Stem-and-Leaf Display Box-and-Whisker Plot Quartiles Percentiles 2.8 Writing Research Reports Background Statement Design and Procedures of the Study Results Analysis and Discussion Conclusions and Recommendations Excel Excitement Summary Exercises Research Reports Endnotes Chapter Three: Probability 3.1 Probability Defined: Empirically Subjective Probability 3.2 Probability Defined: Classically Two Fundamental Properties AND and OR Statements Practice Exercises Use of Mathematical Formulas in Simple Experiments 3.3 More Complex Experiments: Tree Diagram 3.4 More Complex Experiments: Multiplication Rules Dependent and Independent Events Counting Principle 3.5 Early Gambling Experiments Leading to Discovery of the Normal Curve 3.6 Additional Probability Topics Mean and Standard Deviation of a Discrete Probability Distribution Expected Value Permutations and Combinations Summary Exercises Chapter Four: Normal Distribution 4.0 Origins of the Concept 4.1 Idealized Normal Curve Characteristics of the Normal Curve Use of the Normal Curve Table 4.2 Applications: Idealized Normal Curve 4.3 Working Backward with the Normal Curve Table Applications 4.4 Binomial Distribution: An Introduction to Sampling Sampling from a Two-Category Population Terminology 4.5 Binomial Sampling Distribution: Applications Excel Excitement Summary Exercises Endnotes Chapter Five: Central Limit Theorem 5.1 Central Limit Theorem 5.2 Applying the Central Limit Theorem Random Selection 5.3 How n and ? Affect ?x- How ? Affects ?x- How n Affects ?x- 5.4 Central Limit Theorem Applied to Nonnormal Populations Excel Excitement Summary Exercises Endnotes Chapter Six: Introduction to Hypothesis Testing 6.1 Basic Concepts of Hypothesis Testing Accept/Reject Decision Making Type I Error Type II Error Power 6.2 Applications 6.3 Controlling Error Excel Excitement Summary Exercises Chapter Seven: Hypothesis Testing 7.1 Two-Tailed Hypothesis Tests ( Large Sample, n ? 30) Method One: The P-Value Method Methods Two and Three: The Classical Methods Control Charts 7.2 One-Tailed Hypothesis Tests (Large Sample, n ? 30) Applications Method One: The P-Value Method Methods Two and Three: The Classical Methods Control Charts 7.3 Small-Sample Hypothesis Tests (n < 30) Applications Method One: The P-Value Method Methods Two and Three: The Classical Methods Starting from Raw Data Method One: The P-Value Method Methods Two and Three: The Classical Methods Excel Excitement Summary Exercises Endnotes Chapter Eight: Confidence Intervals 8.1 Confidence Interval for ? 8.2 Applications 8.3 Selecting Sample Size 8.4 Confidence Intervals Using Small Samples (n , 30) Assurance of Normal or Near Normal Population t Score Compensation When s Is Used to Estimate s Starting from Raw Data Excel Excitement Summary Exercises Endnotes Chapter Nine: Regression and Correlation 9.0 Origins of the Concept Galton's Parent-Off spring Height Experiment Application to Statistics Least-Squares Analysis Yule's Application to Social Issues Correlation Does Not Prove Cause and Effect 9.1 Graphing: A Brief Review 9.2 Simple Linear Regression: Organizing and Analyzing Bivariate Data Overview Simple Linear Regression 9.3 Simple Linear Regression: Correlation and Related Topics r, The Linear Correlation Coefficient Test of Significance for r r 2, A Measure of Explained Variation Summary and Discussion 9.4 Using Samples to Estimate Population Characteristics 9.5 Multiple Linear Regression: Organizing and Analyzing Multivariate Data Simple Linear Regression (Brief Summary) Multiple Regression Predicting the Dependent Variable Interpreting the y-Intercept and Slopes r 2 in Multiple Regression Geometric Visualization of Multiple Regression Adjusted r2 Making Inferences with the Population Regression Coefficients Excel Excitement Summary Exercises Endnotes Chapter Ten: Analysis of Variance 10.1 Measurement Population Sampling: The Idea Behind ANOVA Difference of Two Population Means (Independent Case) Difference of Two Population Means (Dependent Case) 10.2 One-Way Analysis of Variance (ANOVA) for Equal Sample Sizes Overview of ANOVA Test Logic of ANOVA Sum-of-Squared Distances 10.3 One-Way Analysis of Variance (ANOVA) for Unequal Sample Sizes 10.4 Tukey's Multiple Comparisons Method for One-Way ANOVA Rejecting H0: Taking a Closer Look Tukey Defined Tukey Applied 10.5 Two-Way Analysis of Variance (ANOVA) One-Way ANOVA (Brief Summary) Two-Way ANOVA The Mathematics Behind Variation Sources Analyzing Sources of Variation 10.6 Tukey's Multiple Comparisons Methods for Two-Way ANOVA The Factor A and Factor B Effects: Tukey and Interaction Tukey and Factor A Tukey and Factor B Excel Excitement Summary Exercises Endnotes Answer Key Statistical Tables Normal Curve (z) Table t Table F Table (? = 0.05) F Table (? = 0.01) Q Table (? = 0.05) Q Table (? = 0.01) Spearman's rs Table Binomial Tables Chi-Square Table r Table Random Numbers Table Index

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