A First Course in Statistics
United States Edition
8th Edition
Published on 27. June 2002
Book
Hardback
576 pages
978-0-13-065596-7 (ISBN)
Description
For courses in Statistics.
This introduction to statistics presents balanced coverage of both the theory and application of statistics and at the same time helps students develop and enhance their critical thinking skills. It shows students how to analyze data that appear in situations in the world around them and features an abundance of examples and exercises-nearly all based on current, real-world applications pulled from journals, magazines, news articles, and commerce.
This introduction to statistics presents balanced coverage of both the theory and application of statistics and at the same time helps students develop and enhance their critical thinking skills. It shows students how to analyze data that appear in situations in the world around them and features an abundance of examples and exercises-nearly all based on current, real-world applications pulled from journals, magazines, news articles, and commerce.
More details
Edition
8th edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 262 mm
Width: 209 mm
Thickness: 27 mm
Weight
1262 gr
ISBN-13
978-0-13-065596-7 (9780130655967)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
James T. McClave | Terry Sincich
A First Course in Statistics
Book
06/2005
9th Edition
Pearson
€59.41
Article exhausted; check for reprint
Previous edition
Book
06/2002
8th Edition
Pearson
€63.08
Article exhausted; check for reprint
Content
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.
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.
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.
4. Random Variables and Probability Distribution.
Two Types of Random Variables. Probability Distributions for Discrete Random Variables. The Binomial Random Variable. Continuous Probability Distributions. The Normal Distribution. Descriptive Methods for Assessing Normality. Approximating a Binomial Distribution with a Normal Distribution (Optional). Sampling Distributions. The Central Limit Theorem.
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.
6. Inferences Based on a Single Sample: Tests of Hypotheses.
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. Nonparametric Test about a Population Median (Optional).
7. Comparing Population Means.
Comparing Two Population Means: Independent Sampling. Comparing Two Population Means: Paired Difference Experiments. Determining the Sample Size. 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).
8. Comparing Population Proportions.
Comparing Two Population Proportions: Independent Sampling. Determining the Sample Size. Comparing Population Proportions: Multinomial Experiment. Contingency Table Analysis.
9. Simple Linear Regression.
Probabalistic Models. Fitting the Model: The Least Squares Approach. Model Assumptions. An Estimator of ...s2. Assessing the Utility of the Model: Making Inferences about the Slope ...b1. The Coefficient of Correlation. The Coefficient of Determination. Using the Model for Estimation and Prediction. A Complete Example. A Nonparametric Test for Correlation (Optional).
Appendix A. Tables.
Random Numbers. Binomial Probabilities. Normal Curve Areas. Critical Values of t. Critical Values of ...c2. Percentage Points of the F Distribution, ...a= .10. Percentage Points of the F Distribution, ...a=.05. Percentage Points of the F Distribution, ...a=.025. Percentage Points of the F Distribution, ...a=.01. Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples. Critical Values of TO in the Wilcoxon Paired Difference Signed Rank Test. Critical Values of Spearman's Rank Correlation Coefficient.
Appendix B. Data Sets on CD-ROM that Accompany this Text.
Appendix C. Calculation Formulas for Analysis of Variance.
Short Answers to Selected Odd-Numbered Exercises.
Index.
The Science of Statistics. Types of Statistical Applications. Fundamental Elements of Statistics. Types of Data. Collecting Data. The Role of Statistics in Critical Thinking.
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.
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.
4. Random Variables and Probability Distribution.
Two Types of Random Variables. Probability Distributions for Discrete Random Variables. The Binomial Random Variable. Continuous Probability Distributions. The Normal Distribution. Descriptive Methods for Assessing Normality. Approximating a Binomial Distribution with a Normal Distribution (Optional). Sampling Distributions. The Central Limit Theorem.
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.
6. Inferences Based on a Single Sample: Tests of Hypotheses.
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. Nonparametric Test about a Population Median (Optional).
7. Comparing Population Means.
Comparing Two Population Means: Independent Sampling. Comparing Two Population Means: Paired Difference Experiments. Determining the Sample Size. 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).
8. Comparing Population Proportions.
Comparing Two Population Proportions: Independent Sampling. Determining the Sample Size. Comparing Population Proportions: Multinomial Experiment. Contingency Table Analysis.
9. Simple Linear Regression.
Probabalistic Models. Fitting the Model: The Least Squares Approach. Model Assumptions. An Estimator of ...s2. Assessing the Utility of the Model: Making Inferences about the Slope ...b1. The Coefficient of Correlation. The Coefficient of Determination. Using the Model for Estimation and Prediction. A Complete Example. A Nonparametric Test for Correlation (Optional).
Appendix A. Tables.
Random Numbers. Binomial Probabilities. Normal Curve Areas. Critical Values of t. Critical Values of ...c2. Percentage Points of the F Distribution, ...a= .10. Percentage Points of the F Distribution, ...a=.05. Percentage Points of the F Distribution, ...a=.025. Percentage Points of the F Distribution, ...a=.01. Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples. Critical Values of TO in the Wilcoxon Paired Difference Signed Rank Test. Critical Values of Spearman's Rank Correlation Coefficient.
Appendix B. Data Sets on CD-ROM that Accompany this Text.
Appendix C. Calculation Formulas for Analysis of Variance.
Short Answers to Selected Odd-Numbered Exercises.
Index.