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Unformatted text preview: Biostatistics 100B, Midterm 2 Practice Problems General Comments: • These problems are taken from old exams from some of my past classes. I have picked a selection of problems that I think will be useful. I do not guarantee that I have here a problem on every subject that is fair game for the exam or that the balance is exactly right. In particular this set is short on interaction questions. I will try to add a few interaction pieces later but in the meantime you can make up interaction problems simply by practicing saying what the interaction between any two variables in a multiple regression problem would mean. • Some of the problems below are repeats from the midterm 1 regression practice but with extra parts on confidence intervals and hypothesis tests included so don’t just skip over them! • In addition to (in fact even more important than) the practice problems it is worth reviewing the problems from HW 46 as the assignments more accurately reflect what I think are the key topics we have covered so far. • The exam will be closed book. However, you may use two pages, front and back, of notes and formulas. Write your answers on the exam sheets. If you need more space, continue your answer on the back of the pages. Normal and t distribution tables will be provided for you at the end of the exam and I will have scratch paper available if you want it. • You must show your work on the exam to obtain full credit. If you use a result from class, state what result you are using. If you can’t complete a problem for any reason, explain what concepts are at issue, and how you would attack the problem. If you can’t work out a number you need for a later part of a problem give it a symbol and show how you would do the calculations with a symbol in place of the missing number. It is, in any case, a good idea to explain briefly what your reasoning is in English. If I can’t tell that you understood what you were doing, I can’t give you credit, particularly if you get the wrong numerical answer. HAPPY STUDYING! Problem 1: Television Ads You own a chain of stores that sells television sets and you want to know whether your advertising is increasing your sales. Let Y be the number of TVs you sell in a given month, and let X be the amount of money you spend on advertising in a given month in thousands of dollars. You have data on advertising expenditures and sales for n=42 months and have fit a simple linear regression of Y on X. The printout for this regression is given below along with a few useful summary statistics. Use it to answer the following questions: The regression equation is TV Sales = 48.4 + 10.2 AdSpending Parameter Estimates Predictor Coef Stdev tratio p Constant 48.40 17.61 2.75 0.009 1 Ad Spending 10.2457 0.5224 19.61 0.000 Root MSE = 38.54 Rsq = 90.6% Rsq(adj) = 90.3% Analysis of Variance SOURCE DF SS MS F p Regression 1 571411 571411 384.70 0.000 Error 40 59413 1485 Total 41 630824 ******************** Summary Statistics For Number of Televisions Sold Per Month...
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 Winter '07
 Sugar
 Regression Analysis

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