Page of 12 0 - ZOOM + GOODNESS OF FIT scenario based on "known proportion". A psychologist was interested in students' stress-reduction strategies. Of the 60 students surveyed, 20 preferred running, 12 preferred swimming, 18 preferred dancing, and 10 preferred some other activity. Using the .05 significance level, do the results suggest that people prefer different stress-reduction strategies in general? Assume we know the population values and use those proportions to determine the expected frequency of each category. 7. Construct the table with the data reported above, including the expected frequency noted below each observed frequency. Put the expected value in parentheses. For this, we DO know the proportion in the full population. Running tends to be 40%, Swimming at 15%, Dancing is 20%, Other is 25%. This means we give an expected score that is our total frequency multiplied by its expected proportion. For example, if our total frequency is 80 and the percentage expected to be in one category is 30% then we calculate 80 x .30 = 24 as the expected frequency for that category Running Swimming Dancing Other Activity 18 10 Total f = 8. What is the chi-square value for this scenario? * = To determine the value, complete the chart below (rounding each item in the last column to "2 decimal places out"... for example, 3.44826 would be rounded to 3.45) CATEGORY O E (0-E) (0-E) (0-E)/E Running 20 Swimming 12 Dancing 18 Other activity 10 TOTAL 9. What is the of for this scenario? C-1 = 10. What is the critical value? ' needed (df= _a= .05) = 11. Can we reject the null hypothesis? Why or why not? And what does this mean? 12. Note how this would be reported in a journal for just the statistic part by completing the following using this hint x' (df, n = ?) = ????, p_.05 -P _.05