## An Introduction to Statistical Methods and Data AnalysisOtt and Longnecker’s AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Sixth Edition, provides a broad overview of statistical methods for advanced undergraduate and graduate students from a variety of disciplines who have little or no prior course work in statistics. The authors teach students to solve problems encountered in research projects, to make decisions based on data in general settings both within and beyond the university setting, and to become critical readers of statistical analyses in research papers and in news reports. The first eleven chapters present material typically covered in an introductory statistics course, as well as case studies and examples that are often encountered in undergraduate capstone courses. The remaining chapters cover regression modeling and design of experiments. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version. |

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I am a graduate engineer and needed to use the multicomparision methods. The book is very suer friendly and easy to understand. I got enough help from this book and I recommend it fordepartmental liraries because it will be a good addition in the book archive.

Engr. Muhammad Rehan Adil

Lahore( Pakistan)

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p589, definition of high leverage point and high inflence point.

### Contents

Introduction | 1 |

Collecting Data | 15 |

Summarizing Data | 55 |

Analyzing Data Interpreting the Analyses and Communicating Results | 221 |

Statistical Tables | 1169 |

Answers to Selected Exercises | 1210 |

1250 | |

1254 | |

### Other editions - View all

An Introduction to Statistical Methods and Data Analysis R. Ott,Micheal Longnecker Limited preview - 2008 |

An Introduction to Statistical Methods and Data Analysis R. Ott,Micheal Longnecker Limited preview - 2015 |

An Introduction to Statistical Methods and Data Analysis Michael Longnecker,R. Lyman Ott No preview available - 2001 |

### Common terms and phrases

Analysis of Variance AOV table approximately average binomial boxplot Brand calculations Chapter chi-square Coef coefficient completely randomized design confidence interval correlation data set determine dose drug effect estimate evaluate example experiment experimental units explanatory variables Figure frequency histogram given HGMF histogram independent variables inferences interaction konjac level of factor Mean Square measurements median Minitab multiple regression normal distribution normal probability plot null hypothesis observations obtain p-value Parameter patients percentage population distribution population means Predictor procedure R-Sq R-square random sample random variable randomly assigned randomly selected Refer to Exercise Regression Analysis regression equation regression model reject H0 rejection region research hypothesis sample data sample means sample sizes sampling distribution scatterplot scores significant skewed Solution Source DF standard deviation standard error statistical test StDev sum of squares summarized test statistic Total treatment means Type I error versus yield