A First Course in Statistics

A First Course in Statistics

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For a one-semester, general education Introductory Statistics course.

Drawing students in with its reality-based approach and practicality, this popular text offers a balanced and enlightening examination of the theory and application of statistics. Helping to hone important critical thinking skills, it teaches students how to analyze data that appear in situations in the world around them and bases a majority of its examples and exercises on current, real-world applications pulled from journals, magazines, news articles, and commerce.
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Product details

  • Hardback | 650 pages
  • 203.2 x 254 x 27.94mm | 1,292.73g
  • Pearson
  • United States
  • English
  • 7th edition
  • 0130141577
  • 9780130141576

Table of contents

1. 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. Statistics in Action: A "20/20" View of Survey Results - Fact or Fiction?

2. Methods for Describing Sets of Data.

Describing Qualitative Data. Graphical 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. Methods for Detecting Outliers (Optional). Graphing Bivariate Relationships (Optional). Distorting the Truth with Descriptive Techniques. Statistics In Action: The "Eye Cue" Test: Does Experience Improve Performance?

3. 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. Random Sampling. Some Counting Rules (Optional). Statistics In Action: Game Show Strategy: To Switch or Not to Switch.

4. 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. Descriptive Methods for Assessing Normality. Approximating a Binomial Distribution with a Normal Distribution (Optional). Sampling Distributions. The Central Limit Theorem. Statistics in Action: IQ, Economic Mobility, and the Bell Curve

5. 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. Statistics in Action: Scallops, Sampling, and the Law

6. 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). Statistics in Action: March Madness - Handicapping the NCAA Basketball Tourney.

7. 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). Statistics in Action: On the Trail of the Cockroach

8. Comparing Population Proportions.

Comparing Two Population Proportions: Independent Sampling. Determining the Sample Size. Comparing Population Proportions: Multinomial Experiment (Optional). Contingency Table Analysis (Optional). Statistics in Action: The Level of Agreement Among Movie Reviewers - Thumbs Up or Thumbs Down?

9. Simple Linear Regression.

Probabilistic Models. Fitting the Model: The Least Squares Approach. Model Assumptions. An Estimator of Sigma-squared. Assessing the Utility of the Model: Making Inferences About the Slope Beta-1. The Coefficient of Correlation. The Coefficient of Determination. Using the Model for Estimation and Prediction. A Complete Example. A Nonparametric Test for Correlation (Optional). Statistics in Action: Can "Dowsers" Really Detect Water?

Appendix A. Tables.

Random Numbers. Binomial Probabilities. Normal Curve Areas. Critical Values of t. Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples. Critical Values of T0 in the Wilcoxon Paired Difference Signed Rank Test. Percentage Points of the F Distribution, =.10. Percentage Points of the F Distribution, =.05. Percentage Points of the F Distribution, =.025. Percentage Points of the F Distribution, =.01. Critical Values of 2. Critical Values of Spearman's Rank Correlation Coefficient.

Appendix B. Data Sets.

Coronary Artery Patients' Blood Loss Data. Car & Driver Data. Starting Salaries of USF Graduates. Sealed Milk Bids Data. Federal Trade Commission Rankings of Domestic Cigarette Brands.

Appendix C. Calculation Formulas for Analysis of Variance: Independent Sampling.

Short Answers to Selected Odd-Numbered Exercises.

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