First Course in Statistics, A

by McClave, James T.; Sincich, Terry

• ISBN13: 9780131499799
• ISBN10: 0131499793
• Edition: 9th
• Format: Paperback
• Copyright: 2009-01-01
• Publisher: Prentice Hall

Summary

For algebra-based Introductory Statistics courses. The Ninth Edition of this best selling introductory text features a stronger emphasis on critical thinking and sound decision making through its extensive coverage of data collection and analysis. In addition, it features a balanced approach to both the theory and application of statistics. Incorporating more pedagogy than ever before, the text helps students develop statistical thinking and teaches students to properly assess the credibility of inferences from the vantage point of both the consumer and the producer.

Table of Contents

Statistics, Data, and Statistical Thinking

The Science of Statistics

Types of Statistical Applications

Fundamental Elements of Statistics

Types of Data

Collecting Data

The Role of Statistics in Critical Thinking

Methods for Describing Sets of Data

Describing Qualitative Data

Graphic Methods for Describing Quantitative Data

Summation Notation

Numerical Measures of Central Tendency

Numerical Measures of Variability

Interpreting the Standard Deviation

Numerical Measures of Relative Standing

Quartiles and Box Plots (Optional)

Distorting the Truth with Descriptive Techniques

Probability

Events, Sample Spaces, and Probability

Unions and Intersections

Complementary Events

The Additive Rule and Mutually Exclusive Events

Conditional Probability

The Multiplicative Rule and Independent Events

Probability and Statistics: An Example

Random Sampling

Random Variables and Probability Distributions

Two Types of Random Variables

Probability Distributions for Discrete Random Variables

The Binomial Distribution

Probability Distributions for Continuous Random Variables

The Normal Distribution

Sampling Distributions

Properties of Sampling Distributions: Unbiasedness and Minimum Variance (Optional)

The Central Limit Theorem

Inferences Based on a Single Sample: Estimation with Confidence Intervals

Large-Sample Confidence Interval for a Population Mean

Small- Sample Confidence Interval for a Population Mean

Large-Sample Confidence Interval for a Population Proportion

Determining the Sample Size

Inferences Based on a Single Sample: Tests of Hypothesis

The Elements of a Test of Hypothesis

Large-Sample Test of Hypothesis About a Population Mean

Observed Significance Levels: p- Values

Small-Sample Test of Hypothesis About a Population Mean

Large-Sample Test of Hypothesis About a Population Proportion

A Nonparametric Test About a Population Median (Optional)

Comparing Population Means

Comparing Two Population Means: Independent Sampling

Comparing Two Population Means: Paired Difference Experiments

Determining the Sample Size

A Nonparametric Test for Comparing Two Populations: Independent Sampling (Optional)

A Nonparametric Test for Comparing Two Populations: Paired Difference Experiments (Optional)

Comparing Three or More Population Means: Analysis of Variance (Optional)

Comparing Population Proportions

Comparing Two Population Proportions: Independent Sampling

Determining the Sample Size

Comparing Population Proportions: Multinomial Experiment (Optional)

Contingency Table Analysis (Optional)

Simple Linear Regression

Probabilistic Models

Fitting the Model: The Least Squares Approach

Model Assumptions

An Estimator of âÇ s2

Assessing the Utility of the Model: Making Inferences About the Slope âÇ b1

The Coefficient of Correlation

The Coefficient of Determination

Using the Model for Estimation and Prediction

Simple Linear Regression: An Example

A Nonparametric Test for Correlation (Optional)

Tables

Data Sets

Calculation Formulas for Analysis of Variance: Independent Sampling

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