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Unformatted text preview: 2 of 14 1.1 Review 14. confidence interval for proportion 15. confidence interval for difference in proportions 16. one sample mean test 17. two independent sample mean test 18. match pair test 19. one sample proportion test 20. two sample proportion test 21. test of homogeneity 22. test of independence 23. linear correlation coefficient & test 24. regression For each situation below, which method is most applicable? • If it’s a hypothesis test, what are the null and alternative (state in words and mathematically). • If it’s a graphical method, describe what you would be looking for. Question 1 . A college admission board wants to determine if student A with a GPA of 3.4 at a tough public school with an average student GPA of 2.2 and standard deviation of 0.5 is better than student B with a GPA of 3.9 from a easy private school with an average student GPA of 3.3 and standard deviation of 0.4 Question 2 . A scientist wants to determine if the length of penguin beaks are normally distributed. Question 3 . A bad comedian who can’t find work decides to do a study to determine if the style of shoe a person wears depends on hair color. Question 4 . A student is wring a report on Tucson, they need to find a number Anthony Tanbakuchi MAT167 Analysis of Variance 3 of 14 to describe how much the maximum daily temperature varies throughout the year. Question 5 . A professor wants to compare the distribution of Exam II scores for two sections of the same statistics class. 1.2 Introduction Figure 1: ANOVA Comic (Credit: Jorge Cham http://phdcomics.com ) Example 1 . A clinical psychologist wishes to test three methods (A, B, C) for reducing hostility levels in university students to see if there is any real difference between the methods. A certain psychological test (HLT) was used Anthony Tanbakuchi MAT167 4 of 14 1.2 Introduction to measure the degree of hostility (higher scores indicate greater hostility).to measure the degree of hostility (higher scores indicate greater hostility)....
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 Spring '11
 Tanbakuchi
 Statistics, Normal Distribution, Type I and type II errors, Male Female Male, Anthony Tanbakuchi

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