Test Bank for Statistics 13th Edition by James McClave 0134090438 9780134090436

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ISBN 10: 0134090438
ISBN 13: 9780134090436

Author: James McClave

For courses in introductory statistics.   A Contemporary Classic Classic, yet contemporary; theoretical, yet applied–McClave & Sincich’s Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. This new edition is extensively revised with an eye on clearer, more concise language throughout the text and in the exercises. Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra. Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory.   Also available with MyStatLab MyStatLab™ is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. For this edition, MyStatLab offers 25% new and updated exercises.   Note: You are purchasing a standalone product; MyLab™ & Mastering™ does not come packaged with this content. Students, if interested in purchasing this title with MyLab & Mastering, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. 

Statistics 13th Table of contents:

1 Statistics, Data, and Statistical Thinking
1.1 The Science of Statistics
1.2 Types of Statistical Applications
1.3 Fundamental Elements of Statistics
1.4 Types of Data
1.5 Collecting Data: Sampling and Related Issues
1.6 The Role of Statistics in Critical Thinking and Ethics
2 Methods for Describing Sets of Data
2.1 Describing Qualitative Data
2.2 Graphical Methods for Describing Quantitative Data
2.3 Numerical Measures of Central Tendency
2.4 Numerical Measures of Variability
2.5 Using the Mean and Standard Deviation to Describe Data
2.6 Numerical Measures of Relative Standing
2.7 Methods for Detecting Outliers: Box Plots and z-Scores
2.8 Graphing Bivariate Relationships (Optional)
2.9 Distorting the Truth with Descriptive Statistics
3 Probability
3.1 Events, Sample Spaces, and Probability
3.2 Unions and Intersections
3.3 Complementary Events
3.4 The Additive Rule and Mutually Exclusive Events
3.5 Conditional Probability
3.6 The Multiplicative Rule and Independent Events
3.7 Some Additional Counting Rules (Optional)
3.8 Bayes’s Rule (Optional)
4.1 Two Types of Random Variables
4.2 Probability Distributions for Discrete Random Variables
4.3 Expected Values of Discrete Random Variables
4.4 The Binomial Random Variable
4.5 The Poisson Random Variable (Optional)
4.6 The Hypergeometric Random Variable (Optional)
5 Continuous Random Variables
5.1 Continuous Probability Distributions
5.2 The Uniform Distribution
5.3 The Normal Distribution
5.5 Approximating a Binomial Distribution with a Normal Distribution
5.6 The Exponential Distribution (Optional)
6 Sampling Distributions
6.1 The Concept of a Sampling Distribution
6.2 Properties of Sampling Distributions: Unbiasedness and Minimum
6.3 The Sampling Distribution of x¯ and the Central Limit Theorem
6.4 The Sampling Distribution of the Sample Proportion
7 Inferences Based on a Single Sample Estimation with Confidence
7.1 Identifying and Estimating the Target Parameter
7.2 Confidence Interval for a Population Mean: Normal (z) Statistic
7.3 Confidence Interval for a Population Mean: Student’s t-Statistic
7.4 Large-Sample Confidence Interval for a Population Proportion
7.5 Determining the Sample Size
7.6 Confidence Interval for a Population Variance (Optional)
8 Inferences Based on a Single Sample Tests of Hypothesis
Contents
8.1 The Elements of a Test of Hypothesis
8.2 Formulating Hypotheses and Setting Up the Rejection Region
8.3 Observed Significance Levels: p-Values
9 Inferences Based on Two Samples Confidence Intervals and Tests of 
9.1 Identifying the Target Parameter
9.2 Comparing Two Population Means: Independent Sampling
9.3 Comparing Two Population Means: Paired Difference Experiments
9.4 Comparing Two Population Proportions: Independent Sampling
9.5 Determining the Sample Size
9.6 Comparing Two Population Variances: Independent Sampling 
10 Analysis of Variance Comparing More than Two Means
10.1 Elements of a Designed Study
10.2 The Completely Randomized Design: Single Factor
10.3  Multiple Comparisons of Means
10.4 The Randomized Block Design
10.5 Factorial Experiments: Two Factors
11 Simple Linear Regression
11.1 Probabilistic Models
11.2 Fitting the Model: The Least Squares Approach
11.3 Model Assumptions
11.4 Assessing the Utility of the Model: Making Inferences about the 
11.5 The Coefficients of Correlation and Determination
11.6 Using the Model for Estimation and Prediction
11.7 A Complete Example
12 Multiple Regression and Model Building
12.1 Multiple-Regression Models
12.2 Estimating and Making Inferences about the β Parameters
12.3 Evaluating Overall Model Utility
12.4 Using the Model for Estimation and Prediction
12.5 Interaction Models
13 Categorical Data Analysis
13.1 Categorical Data and the Multinomial Experiment
13.2 Testing Categorical Probabilities: One-Way Table
13.3 Testing Categorical Probabilities: Two-Way (Contingency) Table
13.4 A Word of Caution about Chi-Square Tests
14 Nonparamtric Statistics
14.1 Introduction: Distribution-Free Tests
14.2 Single-Population Inferences
14.3 Comparing Two Populations: Independent Samples
14.4 Comparing Two Populations: Paired Difference Experiment
14.5 Comparing Three or More Populations: Completely Randomized 
14.6 Comparing Three or More Populations: Randomized Block Design

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