Elementary Statistics

Description

Bluman A.G. Elementary Statistics: A Step By Step Approach Copyright About the Author Contents Preface Chapter 1 The Nature of Probability and Statistics Introduction 1–1 Descriptive and Inferential Statistics 1–2 Variables and Types of Data 1–3 Data Collection and Sampling Techniques Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling Other Sampling Methods 1–4 Experimental Design Observational and Experimental Studies Uses and Misuses of Statistics 1–5 Computers and Calculators Summary Chapter 2 Frequency Distributions and Graphs Introduction 2–1 Organizing Data Categorical Frequency Distributions Grouped Frequency Distributions 2–2 Histograms, Frequency Polygons, and Ogives The Histogram The Frequency Polygon The Ogive Relative Frequency Graphs Distribution Shapes 2–3 Other Types of Graphs Bar Graphs Pareto Charts The Time Series Graph The Pie Graph Dotplots Stem and Leaf Plots Misleading Graphs Summary Chapter 3 Data Description Introduction 3–1 Measures of Central Tendency The Mean The Median The Mode The Midrange The Weighted Mean Distribution Shapes 3–2 Measures of Variation Range Population Variance and Standard Deviation Sample Variance and Standard Deviation Variance and Standard Deviation for Grouped Data Coefficient of Variation Range Rule of Thumb Chebyshev's Theorem The Empirical (Normal) Rule Linear Transformation of Data 3–3 Measures of Position Standard Scores Percentiles Quartiles and Deciles Outliers 3–4 Exploratory Data Analysis The Five-Number Summary and Boxplots Summary Chapter 4 Probability and Counting Rules Introduction 4–1 Sample Spaces and Probability Basic Concepts Classical Probability Complementary Events Empirical Probability Law of Large Numbers Subjective Probability Probability and Risk Taking 4–2 The Addition Rules for Probability 4–3 The Multiplication Rules and Conditional Probability The Multiplication Rules Conditional Probability Probabilities for "At Least" 4–4 Counting Rules The Fundamental Counting Rule Factorial Notation Permutations Combinations 4–5 Probability and Counting Rules Summary Chapter 5 Discrete Probability Distributions Introduction 5–1 Probability Distributions 5–2 Mean, Variance, Standard Deviation, and Expectation Mean Variance and Standard Deviation Expectation 5–3 The Binomial Distribution 5–4 Other Types of Distributions The Multinomial Distribution The Poisson Distribution The Hypergeometric Distribution The Geometric Distribution Summary Chapter 6 The Normal Distribution Introduction 6–1 Normal Distributions The Standard Normal Distribution Finding Areas Under the Standard Normal Distribution Curve A Normal Distribution Curve as a Probability Distribution Curve 6–2 Applications of the Normal Distribution Finding Data Values Given Specific Probabilities Determining Normality 6–3 The Central Limit Theorem Distribution of Sample Means Finite Population Correction Factor (Optional) 6–4 The Normal Approximation to the Binomial Distribution Summary Chapter 7 Confidence Intervals and Sample Size Introduction 7–1 Confidence Intervals for the Mean When σ Is Known Confidence Intervals Sample Size 7–2 Confidence Intervals for the Mean When σ Is Unknown 7–3 Confidence Intervals and Sample Size for Proportions Confidence Intervals Sample Size for Proportions 7–4 Confidence Intervals for Variances and Standard Deviations Summary Chapter 8 Hypothesis Testing Introduction 8–1 Steps in Hypothesis Testing—Traditional Method 8–2 z Test for a Mean P-Value Method for Hypothesis Testing 8–3 t Test for a Mean 8–4 z Test for a Proportion 8–5 X[sup(2)] Test for a Variance or Standard Deviation 8–6 Additional Topics Regarding Hypothesis Testing Confidence Intervals and Hypothesis Testing Type II Error and the Power of a Test Summary Chapter 9 Testing the Difference Between Two Means, Two Proportions, and Two Variances Introduction 9–1 Testing the Difference Between Two Means: Using the z Test 9–2 Testing the Difference Between Two Means of Independent Samples: Using the t Test 9–3 Testing the Difference Between Two Means: Dependent Samples 9–4 Testing the Difference Between Proportions 9–5 Testing the Difference Between Two Variances Summary Chapter 10 Correlation and Regression Introduction 10–1 Scatter Plots and Correlation Correlation 10–2 Regression Line of Best Fit Determination of the Regression Line Equation 10–3 Coefficient of Determination and Standard Error of the Estimate Types of Variation for the Regression Model Residual Plots Coefficient of Determination Standard Error of the Estimate Prediction Interval 10–4 Multiple Regression (Optional) The Multiple Regression Equation Testing the Significance of R Adjusted R[sup(2)] Summary Chapter 11 Other Chi-Square Tests Introduction 11–1 Test for Goodness of Fit Test of Normality (Optional) 11–2 Tests Using Contingency Tables Test for Independence Test for Homogeneity of Proportions Summary Chapter 12 Analysis of Variance Introduction 12–1 One-Way Analysis of Variance 12–2 The Scheffé Test and the Tukey Test Scheffé Test Tukey Test 12–3 Two-Way Analysis of Variance Summary Chapter 13 Nonparametric Statistics Introduction 13–1 Advantages and Disadvantages of Nonparametric Methods Advantages Disadvantages Ranking 13–2 The Sign Test Single-Sample Sign Test Paired-Sample Sign Test 13–3 The Wilcoxon Rank Sum Test 13–4 The Wilcoxon Signed-Rank Test 13–5 The Kruskal-Wallis Test 13–6 The Spearman Rank Correlation Coefficient and the Runs Test Rank Correlation Coefficient The Runs Test Summary Chapter 14 Sampling and Simulation Introduction 14–1 Common Sampling Techniques Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling Other Types of Sampling Techniques 14–2 Surveys and Questionnaire Design 14–3 Simulation Techniques and the Monte Carlo Method The Monte Carlo Method Summary Appendices A. Tables B. Data Bank C. Glossary D. Selected Answers Index A B C D E F G H I K L M N O P Q R S T U V W Y Z Glossary of Symbols Important Formulas