Introduction | p. 1 |

Statistics | p. 1 |

Descriptive Statistics | p. 1 |

Inferential Statistics: Population and Sample | p. 1 |

Variable, Observation, and Data Set | p. 2 |

Quantitative Variable: Discrete and Continuous Variable | p. 3 |

Qualitative Variable | p. 4 |

Nominal, Ordinal, Interval, and Ratio Levels of Measurement | p. 5 |

Summation Notation | p. 6 |

Computer Software and Statistics | p. 8 |

Organizing Data | p. 16 |

Raw Data | p. 16 |

Frequency Distribution for Qualitative Data | p. 16 |

Relative Frequency of a Category | p. 17 |

Percentage | p. 17 |

Bar Graph | p. 17 |

Pie Chart | p. 18 |

Frequency Distribution for Quantitative Data | p. 19 |

Class Limits, Class Boundaries, Class Marks, and Class Width | p. 20 |

Single-Valued Classes | p. 21 |

Histograms | p. 22 |

Cumulative Frequency Distributions | p. 24 |

Cumulative Relative Frequency Distributions | p. 24 |

Ogives | p. 24 |

Stem-and-Leaf Displays | p. 25 |

Descriptive Measures | p. 46 |

Measures of Central Tendency | p. 46 |

Mean, Median, and Mode for Ungrouped Data | p. 46 |

Measures of Dispersion | p. 48 |

Range, Variance, and Standard Deviation for Ungrouped Data | p. 49 |

Measures of Central Tendency and Dispersion for Grouped Data | p. 51 |

Chebyshev's Theorem | p. 52 |

Empirical Rule | p. 53 |

Coefficient of Variation | p. 53 |

Z Scores | p. 53 |

Measures of Position: Percentiles, Deciles, and Quartiles | p. 54 |

Interquartile Range | p. 56 |

Box-and-Whisker Plot | p. 56 |

Probability | p. 71 |

Experiment, Outcomes, and Sample Space | p. 71 |

Tree Diagrams and the Counting Rule | p. 71 |

Events, Simple Events, and Compound Events | p. 73 |

Probability | p. 73 |

Classical, Relative Frequency and Subjective Probability Definitions | p. 74 |

Marginal and Conditional Probabilities | p. 76 |

Mutually Exclusive Events | p. 77 |

Dependent and Independent Events | p. 78 |

Complementary Events | p. 79 |

Multiplication Rule for the Intersection of Events | p. 79 |

Addition Rule for the Union of Events | p. 80 |

Bayes' Theorem | p. 81 |

Permutations and Combinations | p. 82 |

Using Permutations and Combinations to Solve Probability Problems | p. 83 |

Discrete Random Variables | p. 98 |

Random Variable | p. 98 |

Discrete Random Variable | p. 98 |

Continuous Random Variable | p. 99 |

Probability Distribution | p. 99 |

Mean of a Discrete Random Variable | p. 100 |

Standard Deviation of a Discrete Random Variable | p. 101 |

Binomial Random Variable | p. 102 |

Binomial Probability Formula | p. 103 |

Tables of the Binomial Distribution | p. 105 |

Mean and Standard Deviation of a Binomial Random Variable | p. 106 |

Poisson Random Variable | p. 106 |

Poisson Probability Formula | p. 107 |

Hypergeometric Random Variable | p. 108 |

Hypergeometric Probability Formula | p. 109 |

Continuous Random Variables and Their Probability Distributions | p. 124 |

Uniform Probability Distribution | p. 124 |

Mean and Standard Deviation for the Uniform Probability Distribution | p. 125 |

Normal Probability Distribution | p. 126 |

Standard Normal Distribution | p. 128 |

Standardizing a Normal Distribution | p. 132 |

Applications of the Normal Distribution | p. 132 |

Determining the z and x Values When an Area under the Normal Curve is Known | p. 135 |

Normal Approximation to the Binomial Distribution | p. 137 |

Exponential Probability Distribution | p. 139 |

Probabilities for the Exponential Probability Distribution | p. 140 |

Sampling Distributions | p. 152 |

Simple Random Sampling | p. 152 |

Using Random Number Tables | p. 152 |

Using the Computer to Obtain a Simple Random Sample | p. 153 |

Systematic Random Sampling | p. 154 |

Cluster Sampling | p. 154 |

Stratified Sampling | p. 154 |

Sampling Distribution of the Sampling Mean | p. 154 |

Sampling Error | p. 156 |

Mean and Standard Deviation of the Sample Mean | p. 156 |

Shape of the Sampling Distribution of the Sample Mean and the Central Limit Theorem | p. 158 |

Applications of the Sampling Distribution of the Sample Mean | p. 158 |

Sampling Distribution of the Sample Proportion | p. 160 |

Mean and Standard Deviation of the Sample Proportion | p. 161 |

Shape of the Sampling Distribution of the Sample Proportion and the Central Limit Theorem | p. 162 |

Applications of the Sampling Distribution of the Sample Proportion | p. 163 |

Estimation and Sample Size Determination: One Population | p. 179 |

Point Estimate | p. 179 |

Interval Estimate | p. 179 |

Confidence Interval for the Population Mean: Large Samples | p. 179 |

Maximum Error of Estimate for the Population Mean | p. 181 |

The t Distribution | p. 182 |

Confidence Interval for the Population Mean: Small Samples | p. 184 |

Confidence Interval for the Population Proportion: Large Samples | p. 187 |

Determining the Sample Size for the Estimation of the Population Mean | p. 188 |

Determining the Sample Size for the Estimation of the Population Proportion | p. 189 |

Tests of Hypotheses: One Population | p. 200 |

Null Hypothesis and Alternative Hypothesis | p. 200 |

Test Statistic, Critical Values, Rejection and Nonrejection Regions | p. 201 |

Type I and Type II Errors | p. 202 |

Hypothesis Tests about a Population Mean: Large Samples | p. 207 |

Calculating Type II Errors | p. 209 |

P Values | p. 212 |

Hypothesis Tests about a Population Mean: Small Samples | p. 215 |

Hypothesis Tests about a Population Proportion: Large Samples | p. 217 |

Inferences for Two Populations | p. 229 |

Sampling Distribution of X[subscript 1] - X[subscript 2] for Large Independent Samples | p. 229 |

Estimation of [mu subscript 1] - [mu subscript 2] Using Large Independent Samples | p. 230 |

Testing Hypothesis about [mu subscript 1] - [mu subscript 2] Using Large Independent Samples | p. 232 |

Sampling Distribution of X[subscript 1] - X[subscript 2] for Small Independent Samples from Normal Populations with Equal (but unknown) Standard Deviations | p. 233 |

Estimation of [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Equal (but unknown) Standard Deviations | p. 234 |

Testing Hypothesis about [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Equal (but Unknown) Standard Deviations | p. 235 |

Sampling Distribution of X[subscript 1] - X[subscript 2] for Small Independent Samples from Normal Populations with Unequal (and Unknown) Standard Deviations | p. 241 |

Estimation of [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Unequal (and Unknown) Standard Deviations | p. 242 |

Testing Hypothesis about [mu subscript 1] - [mu subscript 2] Using Small Independent Samples from Normal Populations with Unequal (and Unknown) Standard Deviations | p. 244 |

Sampling Distribution of d for Nonnally Distributed Differences Computed for Dependent Samples | p. 246 |

Estimation of [mu subscript d] Using Normally Distributed Differences Computed from Dependent Samples | p. 247 |

Testing Hypothesis about [mu subscript d] Using Normally Distributed Differences Computed from Dependent Samples | p. 249 |

Sampling Distribution of P[subscript 1] = P[subscript 2] for Large Independent Samples | p. 251 |

Estimation of P[subscript 1] - P[subscript 2] Using Large Independent Samples | p. 252 |

Testing Hypothesis about P[subscript 1] - P[subscript 2] Using Large Independent Samples | p. 253 |

Chi-Square Procedures | p. 272 |

Chi-square Distribution | p. 272 |

Chi-square Tables | p. 273 |

Goodness-of-Fit Test | p. 274 |

Observed and Expected Frequencies | p. 274 |

Sampling Distribution of the Goodness-of-Fit Test Statistic | p. 275 |

Chi-square Independence Test | p. 278 |

Sampling Distribution of the Test Statistic for the Chi-square Independence Test | p. 279 |

Sampling Distribution of the Sample Variance | p. 282 |

Inferences Concerning the Population Variance | p. 284 |

Analysis of Variance (ANOVA) | p. 299 |

F Distribution | p. 299 |

F Table | p. 300 |

Logic Behind a One-Way ANOVA | p. 302 |

Sum of Squares, Mean Squares, and Degrees of Freedom for a One-Way ANOVA | p. 304 |

Sampling Distribution for the One-Way ANOVA Test Statistic | p. 307 |

Building One-Way ANOVA Tables and Testing the Equality of Means | p. 307 |

Logic Behind a Two-Way ANOVA | p. 311 |

Sum of Squares, Mean Squares, and Degrees of Freedom for a Two-Way ANOVA | p. 314 |

Building Two-Way ANOVA Tables | p. 315 |

Sampling Distributions for the Two-Way ANOVA | p. 316 |

Testing Hypothesis Concerning Main Effects and Interaction | p. 316 |

Regression and Correlation | p. 339 |

Straight Lines | p. 339 |

Linear Regression Model | p. 340 |

Least-Squares Line | p. 342 |

Error Sum of Squares | p. 345 |

Standard Deviation of Errors | p. 346 |

Total Sum of Squares | p. 347 |

Regression Sum of Squares | p. 347 |

Coefficient of Determination | p. 348 |

Mean, Standard Deviation, and Sampling Distribution of the Slope of the Estimated Regression Equation | p. 349 |

Inferences Concerning the Slope of the Population Regression Line | p. 349 |

Estimation and Prediction in Linear Regression | p. 350 |

Linear Correlation Coefficient | p. 350 |

Inference Concerning the Population Correlation Coefficient | p. 354 |

Nonparametric Statistics | p. 368 |

Nonparametric Methods | p. 368 |

Sign Test | p. 369 |

Wilcoxon Signed-Ranks Test for Two Dependent Samples | p. 371 |

Wilcoxon Rank-Sum Test for Two Independent Samples | p. 373 |

Kruskal-Wallis Test | p. 376 |

Rank Correlation | p. 379 |

Runs Test for Randomness | p. 380 |

Binomial Probabilities | p. 397 |

Areas under the Standard Normal Curve from 0 to Z | p. 403 |

Area in the Right Tail under the t Distribution Curve | p. 405 |

Area in the Right Tail under the Chi-square Distribution Curve | p. 407 |

Area in the Right Tail under the F Distribution Curve | p. 409 |

Index | p. 411 |

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