Elementary Statistics: A Step By Step Approach

Cover
Title
Copyright
About the Author
Preface
Index of Applications
Contents (direct linking)
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
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, Exercises, Quiz
APPENDIXES
	A: Tables
		Table A Factorials
		Table B The Binomial Distribution
		Table C The Poisson Distribution
		Table D Random Numbers
		Table E The Standard Normal Distribution
		Table F The t Distribution
		Table G The Chi-Square Distribution
		Table H The F Distribution
		Table I Critical Values for the PPMC
		Table J Critical Values for the Sign Test
		Table K Critical Values for the Wilcoxon Signed-Rank Test
		Table L Critical Values for the Rank Correlation Coefficient
		Table M Critical Values for the Number of Runs
		Table N Critical Values for the Tukey Test
	B: Data Bank
	C: Glossary
	D: Selected Answers
		1-
			1-1
			1-2
			1-3
			1-4
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		2-
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			2-3
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		14-
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Index
Glossary of Symbols
Important Formulas
TABLE E The Standard Normal Distribution
TABLE F The t Distribution
TABLE G The Chi-Square Distribution
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