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Math 260 Final Project

Math 260 Final Project. //name //major //picture (optional). 1a. Confidence Intervals. a) State if you’re doing Means or Proportion. D escribe problem. (Ex: I’ll find a 95% confidence interval for the true mean age of all MA 260 students).

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Math 260 Final Project

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  1. Math 260 Final Project • //name • //major • //picture (optional)

  2. 1a. Confidence Intervals a) State if you’re doing Means or Proportion. Describe problem. (Ex: I’ll find a 95% confidence interval for the true mean age of all MA 260 students).

  3. 1b. Confidence Interval Data(insert data in a table, or attach data: take Print Screen of data,Use “Insert screensheet” on Powerpoint)

  4. 1c. Confidence Interval • sample mean or sample proportion (pick one) • margin of error: ____ • confidence interval • Interpretation (explain in a sentence)

  5. 2a. Hypothesis Test for Means Describe your problem here (ex: “I suspect that the average age of students on campus is more than 19 years old.”)

  6. 2b. Hypothesis test data(attach data: take Print Screen of data,Use “Insert screensheet” on Powerpoint)

  7. 2c. Five step hypothesis test 1. 2. 3. 4. 5.

  8. 3a. Second hypothesis test • Choose either proportion test or difference of means (dependent or independent). (State which one) • State problem (ex: I suspect that less that 10% of student on campus are math majors. I will test this claim at =0.05”)

  9. 3b. Hypothesis test data • (attach data: take Print Screen of data,Use “Insert screensheet” on Powerpoint)

  10. 3c. Five step hypothesis test 1. 2. 3. 4. 5.

  11. 4a. Correlation and Regression • Response variable: • Predictor: • How data was collected • Sampling method

  12. 4b. Regression data(include a sample of at least 20) • (attach data: take Print Screen of data,Use “Insert screensheet” on Powerpoint)

  13. 4c. Correlation and Regression • Minitab calculates that correlation is r= ____ • P value • Interpretation of p value • Minitab calculates the Regression equation as ____________ • We can use the equation to predict. • (pick an appropriate x, and calculate y)

  14. 4d. Regression(attach data: take Print Screen of Minitab’s Fitted Line plot,Use “Insert screensheet” on Powerpoint)

  15. 5a. Multiple Regression • Explain problem • Response variable ___________ • Predictors: • ___________ • ___________ • ___________ • Method of collection of data

  16. 5b. Multiple Regression(insert sample data of at least 20) • (attach data: take Print Screen of data,Use “Insert screensheet” on Powerpoint)

  17. 5c. Multiple Regression • Minitab calculates the regression equation: • A prediction (pick appropriate predictors x1 and x2, and predict y) • R 2 is:______ • Interpretation of R 2

  18. 5d. Multiple RegressionAnalysis of predictors

  19. 6. ANOVA • (describe your study)

  20. 6. ANOVA -- data • (attach data: take Print Screen of data,Use “Insert screensheet” on Powerpoint)

  21. ANOVA(insert Minitab One-way (unstacked) ANOVA analysis)

  22. 6. ANOVA – 5 step test 1. 2. 3. 4. 5.

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