Project 4 Simple Regression and Project 5 Hot Hand (2015)

| November 9, 2018

Project 4Simple Regression1. Gather at least 30 data points of data on some sports related activity that has two halves, such as a game or a season. Enter the source of the data. a. If your data is an average; e.g. Earned run average or batting average, do not double. b. If you data is a count: e.g. first half score or home runs in the first half of the season, double the first half number (not the final one).2. Enter the data in the first two columns of a spreadsheet and produce a scatter plot.3. Run a simple regression with the first half variable as the independent variable.4. Paste your results on the assignment sheet.5. Enter the coefficient, standard error and z-statistic.6. Show where your estimate falls on the normal distribution provided.7. Is the coefficient sufficiently different from zero? Explain.8. Is the coefficient sufficiently different from one? Explain. Name __________Assignment SheetAssignment 4Simple Regression1. Variables __________________ __________________2. Source of data __________________3. Regression results4. Coefficient ____________________5. Standard error _____________________6. z-statistic _____________________ 6. Show where zero and one fall on the normal distribution provided. Your estimate is µ, the expected value of the coefficient..wikimedia.org/wikipedia/commons/8/8c/Standard_deviation_diagram.svg”>.svg” 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″>7. Is the coefficient sufficiently different from zero? Explain.8. Is the coefficient sufficiently different from one? Explain.Project 5Hot Hand1. Enter the data on a spreadsheet. Put your name in cell A1 and enter the 1’s and 0’s across the row from B1 to CW1. (You should have done this already.)2. Find your shooting percentage. (Just sum the data and divide by 100). 3. Find the correlation coefficient.a. Paste the data to the second row from A2 to CV2. (Just the data, not your name.)b. (Type =CORREL(B1:CV1, B2:CV2) in an empty cell.4. Find the conditional probabilities for a make following 3 misses, 2 misses, 1 miss, 1 make, 2 makes, 3 makes. You can use the program I provided. Just paste you data over mine in the top row.5. Enter the statistics in the space provided. Note that this is the same data that is in the table on the Philadelphia 76ers in the hot hand article.6. Interpret your results in the space provided.7. Next, count the number of runs in your series. For example the series 11001110 has 4 runs. .8. Go to.quantitativeskills.com/sisa/statistics/ordinal.htm”>http://www.quantitativeskills.com/sisa/statistics/ordinal.htm a. Enter the data and do the WW runs test. b. Find the expected number of runs and the z-statistic. The z-statistic is the number of standard deviations that your outcome lies from the mean of the distribution of runs.9. Show where your runs number falls on the normal distribution provided.10. Enter the statistics in the space provided.11. Interpret your results in the space provided.Name _____________Assignment SheetAssignment #5Hot Hand1. Fill in the followingprob(hit/3 misses) prob(hit/2 misses) p(hit/1 miss) p(hit) p(hit/1hit) p(hit/2 hits) p(hit/3 hits) ?2. Do your conditional probabilities show evidence of the hot hand? Explain.3. Does your correlation coefficient ? show evidence of the hot hand? Explain.4. Fill in the following.hits misses runs expected runs z-statistic5. Show where your runs number falls on the distribution..wikimedia.org/wikipedia/commons/8/8c/Standard_deviation_diagram.svg”>.svg” 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″>6. Is this evidence of the hot hand? Explain.

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