| Preface |
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xv | |
| Acknowledgments |
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xix | |
| About the Authors |
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xxi | |
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Chapter 1 The What and the Why of Statistics |
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1 | (26) |
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2 | (1) |
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Asking Research Questions |
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3 | (1) |
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4 | (1) |
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Formulating the Hypotheses |
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5 | (5) |
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Independent and Dependent Variables: Causality |
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8 | (1) |
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Independent and Dependent Variables: Guidelines |
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9 | (1) |
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10 | (7) |
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10 | (1) |
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Nominal Level of Measurement |
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11 | (1) |
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Ordinal Level of Measurement |
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12 | (1) |
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Interval-Ratio Level of Measurement |
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13 | (1) |
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Cumulative Property of Levels of Measurement |
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13 | (1) |
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Levels of Measurement of Dichotomous Variables |
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14 | (2) |
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Discrete and Continuous Variables |
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16 | (1) |
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A Closer Look 1.1 A Cautionary Note: Measurement Error |
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17 | (1) |
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Analyzing Data and Evaluating the Hypotheses |
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17 | (2) |
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Descriptive and Inferential Statistics |
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18 | (1) |
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Evaluating the Hypotheses |
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19 | (1) |
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Examining a Diverse Society |
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19 | (8) |
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21 | (6) |
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Chapter 2 The Organization and Graphic Presentation of Data |
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27 | (42) |
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27 | (2) |
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Proportions and Percentages |
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29 | (1) |
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30 | (1) |
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The Construction of Frequency Distributions |
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31 | (7) |
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Frequency Distributions for Nominal Variables |
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34 | (1) |
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Frequency Distributions for Ordinal Variables |
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34 | (1) |
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Frequency Distributions for Interval-Ratio Variables |
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35 | (3) |
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38 | (2) |
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40 | (1) |
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41 | (5) |
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How to Construct a Bivariate Table |
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41 | (3) |
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How to Compute Percentages in a Bivariate Table |
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44 | (1) |
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Calculating Percentages Within Each Category of the Independent Variable |
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44 | (1) |
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Comparing the Percentages Across Different Categories of the Independent Variable |
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45 | (1) |
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Graphic Presentation of Data |
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46 | (1) |
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47 | (2) |
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49 | (1) |
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50 | (2) |
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52 | (1) |
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53 | (1) |
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Statistics in Practice: Foreign-Born Population 65 Years and Over |
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54 | (15) |
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A Closer Look 2.1 A Cautionary Note: Distortions in Graphs |
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56 | (1) |
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Data at Work: Spencer Westby: Senior Editorial Analyst |
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57 | (12) |
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Chapter 3 Measures of Central Tendency and Variability |
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69 | (54) |
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Measures of Central Tendency |
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69 | (23) |
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70 | (2) |
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72 | (1) |
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Finding the Median in Sorted Data |
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72 | (4) |
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Finding the Median in Frequency Distributions |
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76 | (1) |
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Locating Percentiles in a Frequency Distribution |
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77 | (1) |
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78 | (3) |
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A Closer Look 3.1 Finding the Mean in a Frequency Distribution |
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81 | (1) |
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Understanding Some Important Properties of the Arithmetic Mean |
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82 | (3) |
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Reading the Research Literature: The Case of Reporting Income |
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85 | (1) |
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Statistics in Practice: The Shape of the Distribution |
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86 | (1) |
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The Symmetrical Distribution |
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86 | (1) |
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The Positively Skewed Distribution |
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87 | (1) |
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The Negatively Skewed Distribution |
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88 | (2) |
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Guidelines for Identifying the Shape of a Distribution |
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90 | (1) |
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Considerations for Choosing a Measure of Central Tendency |
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90 | (1) |
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90 | (1) |
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90 | (1) |
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A Closer Look 3.2 A Cautionary Note: Representing Income |
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91 | (1) |
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92 | (1) |
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92 | (31) |
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The Importance of Measuring Variability |
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93 | (1) |
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94 | (1) |
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95 | (3) |
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98 | (3) |
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The Variance and the Standard Deviation |
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101 | (1) |
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Calculating the Deviation From the Mean |
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102 | (2) |
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Calculating the Variance and the Standard Deviation |
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104 | (2) |
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Considerations for Choosing a Measure of Variation |
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106 | (2) |
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A Closer Look 3.3 More on Interpreting the Standard Deviation |
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108 | (2) |
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Reading the Research Literature: Community College Mentoring |
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110 | (1) |
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Data at Work: Sruthi Chandrasekaran: Senior Research Associate |
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111 | (12) |
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Chapter 4 The Normal Distribution |
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123 | (26) |
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Properties of the Normal Distribution |
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123 | (3) |
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Empirical Distributions Approximating the Normal Distribution |
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124 | (1) |
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Areas Under the Normal Curve |
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124 | (1) |
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Interpreting the Standard Deviation |
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125 | (1) |
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An Application of the Normal Curve |
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126 | (1) |
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Transforming a Raw Score Into a Z Score |
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127 | (1) |
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The Standard Normal Distribution |
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127 | (1) |
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The Standard Normal Table |
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128 | (12) |
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1 Finding the Area Between the Mean and a Positive or Negative Z Score |
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130 | (1) |
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2 Finding the Area Above a Positive Z Score or Below a Negative Z Score |
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131 | (2) |
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3 Transforming Proportions and Percentages Into Z Scores |
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133 | (1) |
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Finding a Z Score That Bounds an Area Above It |
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133 | (1) |
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Finding a Z Score That Bounds an Area Below It |
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134 | (1) |
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4 Working With Percentiles in a Normal Distribution |
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135 | (1) |
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Finding the Percentile Rank of a Score Higher Than the Mean |
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135 | (1) |
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Finding the Percentile Rank of a Score Lower Than the Mean |
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136 | (1) |
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Finding the Raw Score Associated With a Percentile Higher Than 50 |
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137 | (1) |
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Finding the Raw Score Associated With a Percentile Lower Than 50 |
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138 | (2) |
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Reading the Research Literature: Child Health and Academic Achievement |
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140 | (9) |
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A Closer Look 4.1 Percentages, Proportions, and Probabilities |
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140 | (2) |
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Data at Work: Claire Wulf Winiarek: Director of Collaborative Policy Engagement |
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142 | (7) |
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Chapter 5 Sampling and Sampling Distributions |
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149 | (26) |
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149 | (2) |
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Basic Probability Principles |
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151 | (2) |
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153 | (1) |
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154 | (1) |
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The Concept of the Sampling Distribution |
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154 | (4) |
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155 | (1) |
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156 | (1) |
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157 | (1) |
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The Sampling Distribution |
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157 | (1) |
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The Sampling Distribution of the Mean |
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158 | (4) |
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158 | (2) |
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160 | (1) |
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The Mean of the Sampling Distribution |
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161 | (1) |
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The Standard Error of the Mean |
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162 | (1) |
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The Central Limit Theorem |
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162 | (5) |
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165 | (1) |
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The Significance of the Sampling Distribution and the Central Limit Theorem |
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165 | (2) |
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Statistics in Practice: The 2016 U.S. Presidential Election |
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167 | (8) |
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Data at Work: Emily Treichler: Postdoctoral Fellow |
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168 | (7) |
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175 | (26) |
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Point and Interval Estimation |
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176 | (1) |
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Confidence Intervals for Means |
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177 | (9) |
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A Closer Look 6.1 Estimation as a Type Inference |
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178 | (2) |
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Determining the Confidence Interval |
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180 | (1) |
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Calculating the Standard Error of the Mean |
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180 | (1) |
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Deciding on the Level of Confidence and Finding the Corresponding Z Value |
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180 | (1) |
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Calculating the Confidence Interval |
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180 | (1) |
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181 | (1) |
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182 | (2) |
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184 | (1) |
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Calculating the Estimated Standard Error of the Mean |
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184 | (1) |
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Deciding on the Leuel of Confidence and Finding the Corresponding Z Value |
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184 | (1) |
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Calculating the Confidence Interval |
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184 | (1) |
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185 | (1) |
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Sample Size and Confidence Intervals |
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185 | (1) |
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Statistics in Practice: Hispanic Migration and Earnings |
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186 | (4) |
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A Closer Look 6.2 What Affects Confidence Interval Width? |
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189 | (1) |
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Confidence Intervals for Proportions |
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190 | (4) |
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Determining the Confidence Interval |
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192 | (1) |
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Calculating the Estimated Standard Error of the Proportion |
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192 | (1) |
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Deciding on the Desired Level of Confidence and Finding the Corresponding Z Value |
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193 | (1) |
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Calculating the Confidence Interval |
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193 | (1) |
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193 | (1) |
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Reading the Research Literature: Women Victims of Intimate Violence |
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194 | (7) |
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Data at Work: Laurel Person Mecca: Research Specialist |
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196 | (5) |
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Chapter 7 Testing Hypotheses |
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201 | (36) |
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Assumptions of Statistical Hypothesis Testing |
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202 | (1) |
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Stating the Research and Null Hypotheses |
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202 | (3) |
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The Research Hypothesis (H1) |
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203 | (1) |
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204 | (1) |
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Probability Values and Alpha |
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205 | (4) |
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A Closer Look 7.1 More About Significance |
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208 | (1) |
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The Five Steps in Hypothesis Testing: A Summary |
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209 | (4) |
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Errors in Hypothesis Testing |
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210 | (1) |
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The f Statistic and Estimating the Standard Error |
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211 | (1) |
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The t Distribution and Degrees of Freedom |
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212 | (1) |
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Comparing the t and Z Statistics |
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212 | (1) |
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Hypothesis Testing With One Sample and Population Variance Unknown |
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213 | (2) |
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Hypothesis Testing With Two Sample Means |
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215 | (2) |
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The Assumption of Independent Samples |
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216 | (1) |
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Stating the Research and Null Hypotheses |
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216 | (1) |
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The Sampling Distribution of the Difference Between Means |
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217 | (2) |
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Estimating the Standard Error |
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218 | (1) |
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Calculating the Estimated Standard Error |
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218 | (1) |
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218 | (1) |
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Calculating the Degrees of Freedom for a Difference Between Means Test |
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219 | (1) |
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The Five Steps in Hypothesis Testing About Difference Between Means: A Summary |
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219 | (2) |
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A Closer Look 7.2 Calculating the Estimated Standard Error and the Degrees of Freedom (df) When the Population Variances Are Assumed to Be Unequal |
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220 | (1) |
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Statistics in Practice: Vape Use Among Teens |
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221 | (2) |
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Hypothesis Testing With Two Sample Proportions |
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223 | (4) |
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Reading the Research Literature: Reporting the Results of Hypothesis Testing |
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227 | (10) |
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Data at Work: Stephanie Wood: Campus Visit Coordinator |
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229 | (8) |
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Chapter 8 The Chi-Square Test and Measures of Association |
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237 | (42) |
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The Concept of Chi-Square as a Statistical Test |
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239 | (1) |
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The Concept of Statistical Independence |
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240 | (1) |
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The Structure of Hypothesis Testing With Chi-Square |
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241 | (9) |
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241 | (1) |
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Stating the Research and the Null Hypotheses |
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241 | (1) |
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The Concept of Expected Frequencies |
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241 | (1) |
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Calculating the Expected Frequencies |
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242 | (2) |
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Calculating the Obtained Chi-Square |
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244 | (1) |
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The Sampling Distribution of Chi-Square |
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245 | (1) |
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Determining the Degrees of Freedom |
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246 | (2) |
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248 | (1) |
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248 | (2) |
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Statistics in Practice: Respondent and Mother Education |
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250 | (3) |
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A Closer Look 8.1 A Cautionary Note: Sample Size and Statistical Significance for Chi-Square |
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252 | (1) |
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Proportional Reduction of Error |
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253 | (3) |
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A Closer Look 8.2 What Is Strong? What Is Weak? A Guide to Interpretation |
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254 | (2) |
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Lambda: A Measure of Association for Nominal Variables |
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256 | (3) |
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Cramer's V: A Chi-Square-Related Measure of Association for Nominal Variables |
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259 | (1) |
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Gamma and Kendall's Tau-b: Symmetrical Measures of Association for Ordinal Variables |
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259 | (3) |
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Reading the Research Literature: India's Internet-Using Population |
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262 | (17) |
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Data at Work: Patricio Cumsille: Professor |
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264 | (15) |
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Chapter 9 Analysis of Variance |
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279 | (24) |
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Understanding Analysis of Variance |
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280 | (2) |
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The Structure of Hypothesis Testing With ANOVA |
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282 | (6) |
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282 | (1) |
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Stating the Research and the Null Hypotheses and Setting Alpha |
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283 | (1) |
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The Concepts of Between and Within Total Variance |
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283 | (2) |
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285 | (2) |
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A Closer Look 9.1 Decomposition of SST |
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287 | (1) |
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288 | (1) |
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The Five Steps in Hypothesis Testing: A Summary |
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288 | (2) |
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Statistics in Practice: The Ethical Consumer |
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290 | (1) |
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A Closer Look 9.2 Assessing the Relationship Between Variables |
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291 | (1) |
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Reading the Research Literature: College Satisfaction Among Latino Students |
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291 | (12) |
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Data at Work: Kevin Hemminger: Sales Support Manager/Graduate Program in Research Methods and Statistics |
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293 | (10) |
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Chapter 10 Regression and Correlation |
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303 | (46) |
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304 | (1) |
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Linear Relationships and Prediction Rules |
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305 | (9) |
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Finding the Best-Fitting Line |
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306 | (1) |
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307 | (1) |
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A Closer Look 10.1 Other Regression Techniques |
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308 | (1) |
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The Residual Sum of Squares (Le2) |
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309 | (1) |
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309 | (1) |
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309 | (3) |
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A Closer Look 10.2 Understanding the Covariance |
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312 | (1) |
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313 | (1) |
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A Negative Relationship: Age and Internet Hours per Week |
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314 | (3) |
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Methods for Assessing the Accuracy of Predictions |
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317 | (6) |
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Calculating Prediction Errors |
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318 | (4) |
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322 | (1) |
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Testing the Significance of r2 Using ANOVA |
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323 | (4) |
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325 | (1) |
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Pearson's Correlation Coefficient (r) |
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326 | (1) |
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Characteristics of Pearson's r |
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326 | (1) |
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Statistics in Practice: Multiple Regression and ANOVA |
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327 | (5) |
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A Closer Look 10.3 Spurious Correlations and Confounding Effects |
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332 | (1) |
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Reading the Research Literature: Academic Intentions and Support |
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332 | (17) |
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Data at Work: Shinichi Mizokami: Professor |
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334 | (15) |
| Appendix A Table of Random Numbers |
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349 | (4) |
| Appendix B The Standard Normal Table |
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353 | (6) |
| Appendix C Distribution of t |
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359 | (2) |
| Appendix D Distribution of Chi-Square |
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361 | (2) |
| Appendix E Distribution of F |
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363 | (4) |
| Appendix F Basic Math Review (on the website*) Learning Check Solutions |
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367 | (14) |
| Answers to Odd-Numbered Exercises |
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381 | (28) |
| Glossary |
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409 | (6) |
| Notes |
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415 | (6) |
| Index |
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421 | |
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