Applied Regression Modeling, Second Edition by Iain Pardoe(auth.)

By Iain Pardoe(auth.)

Praise for the First Edition

"The cognizance to element is striking. The publication is particularly good written and the writer is very cautious along with his descriptions . . . the examples are wonderful." ?The American Statistician

Fully revised to mirror the newest methodologies and rising purposes, Applied Regression Modeling, moment Edition maintains to focus on some great benefits of statistical tools, in particular regression research and modeling, for figuring out, examining, and examining multivariate info in company, technological know-how, and social technological know-how applications.

The writer makes use of a bounty of real-life examples, case experiences, illustrations, and photographs to introduce readers to the realm of regression research utilizing quite a few software program applications, together with R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a transparent and cautious writing kind, the ebook introduces modeling extensions that illustrate extra complex regression concepts, together with logistic regression, Poisson regression, discrete selection versions, multilevel versions, and Bayesian modeling.

In addition, the Second Edition beneficial properties explanation and enlargement of demanding themes, such as:

  • Transformations, indicator variables, and interaction
  • Testing version assumptions
  • Nonconstant variance
  • Autocorrelation
  • Variable choice methods
  • Model construction and graphical interpretation

Throughout the e-book, datasets and examples were up to date and extra difficulties are incorporated on the finish of every bankruptcy, permitting readers to check their comprehension of the awarded fabric. furthermore, a similar web site gains the book's datasets, presentation slides, designated statistical software program directions, and studying assets together with extra difficulties and tutorial videos.

With an intuitive procedure that isn't heavy on mathematical aspect, Applied Regression Modeling, moment Edition is a superb publication for classes on statistical regression research on the upper-undergraduate and graduate point. The booklet additionally serves as a beneficial source for pros and researchers who make the most of statistical tools for decision-making of their daily work.

Content:
Chapter 1 Foundations (pages 1–33):
Chapter 2 basic Linear Regression (pages 35–82):
Chapter three a number of Linear Regression (pages 83–135):
Chapter four Regression version construction I (pages 137–188):
Chapter five Regression version development II (pages 189–242):
Chapter 6 Case stories (pages 243–266):
Chapter 7 Extensions (pages 267–283):

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Extra info for Applied Regression Modeling, Second Edition

Sample text

For example, for a significance level of 5%: - For an upper-tail test, the critical value is the 95th percentile of the t-distribution with n— 1 degrees of freedom; reject the null in favor of the alternative if the t-statistic is greater than this. - For a lower-tail test, the critical value is the 5th percentile of the t-distribution with n— 1 degrees of freedom; reject the null in favor of the alternative if the t-statistic is less than this. 5th percentile. HYPOTHESIS TESTING 21 As previously, it is perhaps easier to see how all this works by example.

We could extend this analysis to see if there are any features related to the homes that could help us to understand variation in sale prices. For example, it is likely that there is an association between the sale price (in thousands of dollars) for a particular single-family home and the corresponding floor size (in thousands of square feet). It makes more sense to think of sale price as "responding" to floor size rather than the other way around, so we should set the response variable, Y, as sale price, and the predictor variable, X, as floor size.

Computer help #23 in the software information files available from the book website shows how to use statistical software to calculate confidence intervals for the population mean. 6 at the end of this chapter)—you should find that it is ($262,000, $295,000). Now that we've calculated a confidence interval, what exactly does it tell us? " This will get you by among friends (as long as none of your friends happen to be expert statisticians). But to provide a more precise interpretation we have to revisit the notion of hypothetical repeated samples.

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