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[ FreeCourseWeb.com ] Analysis of Variance (Statistics: a Universal Guide to the Unknown Book 15)
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English | 2020 | ASIN: B08B4ZTDW6 | 394 Pages | PDF, EPUB, AZW3 | 24.32 MB
The academic discipline of Statistics is a branch of mathematics that develops and uses techniques for the careful collection, effective presentation, and proper analysis of numerical information. These techniques can be applied to find answers to questions that arise in all areas of human endeavor. Medical researchers use them to test the safety and effectiveness of new drugs or to appraise the effects of lifestyle changes; nutritionists use them to investigate health claims associated with foods or dietary supplements; business executives use them to assess the results of marketing campaigns or the effect of new methods of production on product quality. Economists use them to forecast the business cycle; politicians to predict the outcome of future elections. Spies use them decipher coded messages. The list goes on. No wonder that Statistics has been called a universal guide to the unknown.
Consider your own health, one among millions of topics that Statistics could address. Every day we meet new health-related stories ̶ about prescription and over-the-counter drugs, medical devices and procedures, the lifestyle we should adopt, foods we should favor, and dietary supplements that would surely add years to our lives. Rightly, we dismiss many of these stories as pure snake oil. Mayonnaise prevents Alzheimer’s? Food coloring lowers bad cholesterol? Cinnamon clobbers diabetes? Grapefruit erases breast cancer? Come on! But what about more serious-sounding claims? True enough, reports about ACE inhibitors and beta blockers, Advil and Motrin, 64-slice CT scans and PSA tests, drug-coated stents and the DASH diet appear to be far removed from snake oil, but false claims about any of these may well occur, which makes them snake oil no less than absurd and fantastic claims about mayonnaise and Alzheimer’s.
A knowledge of Statistics offers a remedy. It helps us separate bogus claims from the real thing. The field, however, is so vast that no single book can reasonably cover all of it. Nor can it anticipate which topics will be of interest to any given person. This author, therefore, has divided the field into 24 sections that are made available as separate electronic books from which prospective students and teachers can select the subset that is most useful to them. After reading Book 15 of this series, you will be able to use the analysis of variance, usually called ANOVA, to test whether the means of more than two quantitative populations are equal. Possible approaches include 1. one-way ANOVA, using data derived from experiments based on the randomized group design, in which only one factor (a type of treatment that is deliberately introduced) is believed to affect a variable of interest, 2. two-way ANOVA without interaction, using data derived from experiments based on the randomized block design, in which two factors (a type of treatment deliberately introduced and a single extraneous factor that does not interact with the treatment variable) are believed to affect a variable of interest, 3. two-way ANOVA with interaction, using data derived from experiments based on the randomized block design, in which two factors (a type of treatment deliberately introduced and a single extraneous factor that does interact with the treatment variable) are believed to affect a variable of interest, 4. three-way ANOVA, using data derived from experiments based on the Latin square design, in which three factors (a type of treatment deliberately introduced and two types of extraneous variables) are believed to affect a variable of interest, 5. establishing confidence intervals for individual population means or differences between them, 6. applying Tukey's HSD test to ferret out honestly significant differences between paired sample means.
Book 15 concludes with numerous tests (Practice Problems, True-False and Multiple-Choice questions, and Key Term Recognition Exercises), along with solutions for all.
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