## Applied Statistics for Public PolicyThis practical text provides students with the statistical tools needed to analyze data, and shows how statistics can be used as a tool in making informed, intelligent policy decisions. The authors' approach helps students learn what statistical measures mean and focus on interpreting results, as opposed to memorizing and applying dozens of statistical formulae. The book includes more than 500 end-of-chapter problems, solvable with the easy-to-use Excel spreadsheet application developed by the authors. This template allows students to enter numbers into the appropriate sheet, sit back, and analyze the data. This comprehensive, hands-on textbook requires only a background in high school algebra and has been thoroughly classroom-tested in both undergraduate and graduate level courses. No prior expertise with Excel is required. A disk with the Excel template and the data sets is included with the book, and solutions to the end-of-chapter problems will be provided on the M.E. Sharpe website. |

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### Contents

What Is Statistics All About? | 3 |

Using POLYSTAT to Do Statistical Analysis | 14 |

Presentation of Data | 32 |

Summarizing Data and Using Descriptive Statistics | 70 |

Theory and Applications | 111 |

Sampling and the Normal Distribution | 128 |

Appendix | 141 |

The Central Limit Theorem | 161 |

Validating Hypotheses About a Single Population Proportion | 305 |

Validating Hypotheses About Two Population Proportions | 321 |

Comparing More Than Two Population Means with ANOVA | 341 |

Comparing More Than Two Proportions Using the ChiSquare Test | 372 |

Determining Relationships for Two Variables Using Correlation | 397 |

Measuring Relationships with Simple Regression Analysis | 426 |

Measuring Multivariate Relationships with Regression Analysis | 462 |

Planning Statistical Research | 484 |

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### Common terms and phrases

95 percent actually assume average binomial calculated z-score capita income cells central limit theorem Chapter chi-square coefficient of determination Column confidence interval correlation coefficient critical z-score P(value cross-tabulation data disk data in sheet data set degrees of freedom dependent descriptive statistics equal estimate Example Exercise expectancy F-statistic frequency distribution greater hypothesis test independent variable input large sample less level of confidence level of significance median normal curve normally distributed null hypothesis number of observations one-tail Decision output report percent level POLYSTAT population mean population parameter population proportion population standard deviation probability random sample regression analysis Reject Null reject the null rejection region research hypothesis sample mean sample proportion sample size sample standard deviation sampling error shown in Exhibit skewness small sample Solution square standard error survey test statistic test the hypothesis tion two-tail upper critical two-way ANOVA upper critical z-score voters wants z-distribution

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