Read Online Model Building with Multiple Regression (STATISTICS: A UNIVERSAL GUIDE TO THE UNKNOWN Book 18) MOBI
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? Chelation therapy blasts arterial plaque? Food coloring lowers bad cholesterol? Cinnamon clobbers diabetes? Grapefruit erases breast cancer? Watermelon slashes prostate 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. Consider how glowing press releases of one time, even by renowned medical journals or the FDA, are often followed by conflicting stories at a later time, which makes us ask: Will fancy cholesterol drugs save us from heart attacks or will they destroy our liver? Is the once-a-day baby aspirin the “cure of the century” or a stroke-causing hoax? 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 18 of this series, you will be able to employ multiple regression techniques in a variety of sophisticated ways. Among other things, you will learn to 1. explain the behavior of a dependent variable not only via quantitative independent variables, but also by introducing qualitative independent variables, known as dummy variables, 2. use forward-selection, backward-elimination, and best subset techniques to select the best set of independent variables from among numerous candidates, 3. build simultaneous-equations models containing n unknowns and n independent equations rather than a single equation, 4. recognize simultaneous-equations bias in such multi-equations models, 5. deal with the bias problem by applying the indirect least-squares (ILS) method, 6. recognize the identification problem that often plagues ILS procedures, 7. overcome that problem, in turn, with the help of instrumental variable (IV) methods, such as the two-stage least-squares technique.Book 18 concludes with numerous tests (over 80 Practice Problems, almost 100 True-False and Multiple-Choice questions, and a 27-Key Terms Recognition exercise), along with solutions and answers for all of these.
