McCune - Practice Makes Perfect Statistics

PRACTICE MAKES PERFECT
Statistics

Sandra McCune, Ph.D.

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ISBN: 978-0-07-163817-3

MHID: 0-07-163817-2

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To my beloved parents
Joe and Kathryne Luna

Practice Makes Perfect Statistics is designed as a tool for review and practice in statistics for the beginner or intermediate learner of statistics. It is not intended to introduce concepts, but rather it is meant to reinforce what already has been presented to readers. The topics offered are those that a competent user of statistics needs to know. To that end, this practice workbook is a useful supplementary text for introductory courses in statistics. It can also serve as a refresher text for readers who need to review previously learned statistical concepts and techniques.

Like most topics worth knowing, learning statistics requires diligence and hard work. The foremost purpose of Practice Makes Perfect Statistics is as a source of solved statistics problems. I believe that the best way to develop understanding, while, at the same time, acquiring accuracy and speed in statistics is to work numerous practice exercises. This book has more than 500 practice exercises from beginning to end. A variety of exercises and levels of difficulty are presented to provide reinforcement of statistical concepts. In each unit, a concept discussion followed by example problems precedes each set of exercises to serve as a concise review for readers already familiar with the topics covered. Concepts are broken into basic components to provide ample practice of fundamental skills.

To use Practice Makes Perfect Statistics in the most effective way, it is important that you work through every exercise. After working a set of exercises, use the worked-out solutions to check your understanding of the concepts. I sincerely hope that this book will help you acquire greater competence and confidence in using statistics in your future endeavors.

Sandra Luna McCune, Ph.D.

Descriptive statistics is the branch of statistics that focuses on describing, summarizing, and organizing information. Part I discusses various aspects of descriptive statistics.

Data is a term used to describe information that derives from some form of measurement (counting, using a standard scale, sorting into categories, rank ordering, and so on). You can classify data in several ways according to various qualities. You might classify data as quantitative or qualitative; discrete or continuous; or nominal, ordinal, interval, or ratio level. This chapter describes these different ways of classifying data.

You can classify data as either quantitative or qualitative. Quantitative data are counts or measurements for which representation on a numerical scale is naturally meaningful. Qualitative data consist of labels, category names, ratings, rankings, and such for which representation on a numerical scale is not naturally meaningful. Distinguishing data as quantitative or qualitative is an important skill in statistics.

PROBLEMS

For ae, classify the data as quantitative or qualitative.

a. Daytime temperature readings (in degrees Fahrenheit) in a 30-day period

b. Heights (in centimeters) of plants in a plot of land

c. Satisfaction ratings (on a scale from not satisfied to very satisfied) by users of a website

d. Number (0, 1, 2, or so on) of people attending a conference

e. Party affiliation (Republican, Democrat, Libertarian, or so on) of voters