50 pages of complete step-by-step instructions and videos showing exactly how to perform a variety of advanced regression techniques and how to do them all in Excel. Some of these advanced regression techniques include nonlinear regression, logistic regression, and dummy-variable regression. This e-manual will also clearly explain all of the steps of a regression and how to quickly read the output of regression done in Excel. This e-manual is loaded with completed examples, screenshots, and videos of the advanced regression techniques all being performed in Excel. The instructions, screenshots, and videos are clear and easy-to-follow but at the graduate level. If you are currently taking a difficult graduate-level statistics course that covers advanced regression techniques such as nonlinear regression, logistic regression, or dummy-variable regression, you will find this e-manual to be an outstanding course supplement that will explain these advanced regression techniques much more clearly than your textbook does. If you are a business manager, you will really appreciate how easily and clearly this e-manual will show you how you can perform these advanced regression techniques in Excel to solve difficult statistical problems on your job. Nonlinear regression, logistic regression, and dummy-variable regression are extremely useful in business, but are not widely understood. For example, you can use logistic regression to accurately calculate the probability that your next customer will make a purchase. That use of logistic regression is covered in detail in this e-manual. A detailed model of dummy-variable regression is provided in the e-manual which shows how to calculate how important each attribute of your product is to your customers. Not many people have a working knowledge of these advanced and useful regression techniques. You will. This e-manual will make you an Excel Statistical Master of nonlinear regression, logistic regression, and dummy-variable regression.
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|Size: ||1.7 MB|
|Publisher: ||Excel Master Series|
|Date published: ||Mar 2011|
|ISBN: ||2370003264791 (DRM-PDF)|
|Read Aloud: ||not allowed|