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Unformatted text preview: Statistics 512: Applied Linear Models Topic 1 Topic Overview This topic will cover • Course Overview & Policies • SAS • KNNL Chapter 1 (emphasis on Sections 1.3, 1.6, and 1.7; much should be review) – Simple linear regression; method of least squares (LS) • KNNL Chapter 2 (emphasis on Sections 2.12.9) – Inference in simple linear regression, Prediction intervals and Confidence bands, ANOVA tables, General Linear Test Class Website http://www.stat.purdue.edu/people/jennings/stat512/ Class Policies Refer to handout Overview We will cover • simple linear regression – KNNL Chapters 15 • multiple regression – KNNL Chapters 611 • analysis of variance (ANOVA) – KNNL Chapters 1525 and possibly throw in some other stuff for fun... Emphasis will be placed on using selected practical tools (such as SAS) rather than on mathematical manipulations. We want to understand the theory so that we can apply it appropriately. Some of the material on SLR will be review, but our goal with SLR is to be able to generalize the methods to MLR. SAS SAS is the program we will use to perform data analysis for this class. Learning to use SAS will be a large part of the course. 1 Getting Help with SAS Several sources for help: • SAS Help Files (not always best) • World Wide Web (look up the syntax in your favorite search engine) • SAS Getting Started (in SAS Files section of class website) and Tutorials • Statistical Consulting Service • Evening Help Sessions • Applied Statistics and the SAS Programming Language, 5th edition by Cody and Smith; most relevant material in Chapters 1, 2, 5, 7, and 9. • Your instructor Statistical Consulting Service Math G175 Hours 104 M through F http://www.stat.purdue.edu/scs/ I will often give examples from SAS in class. The pro grams used in lecture (and any other programs you should need) will be available for you to download from the website. I will usually have to edit the output somewhat to get it to fit on the page of notes. You should run the SAS programs yourself to see the real output and experiment with changing the commands to learn how they work. Let me know if you get confused about what is input, output, or my comments. I will tell you the names of all SAS files I use in these notes. If the notes differ from the SAS file, take the SAS file to be correct, since there may be cutandpaste errors. There is a tutorial in SAS to help you get started. Help → Getting Started with SAS Software You should spend some time before next week getting comfortable with SAS (see HW #0). For today, don’t worry about the detailed syntax of the commands. Just try to get a sense of what is going on. Example (Price Analysis for Diamond Rings in Singa pore) Variables • response variable – price in Singapore dollars ( Y ) • explanatory variable – weight of diamond in carats ( X ) 2 Goals • Create a scatterplot • Fit a regression line • Predict the price of a sale for a 0.43 carat diamond ring SAS Data Step...
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 Fall '08
 Staff
 Statistics, Least Squares, Linear Regression, Regression Analysis, Yi, proc reg, yh

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