B outcome variable is categorical support services

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b) Outcome variable is categorical (support services); explanatory variable is binary (gender); = chi-square test of independence c) Outcome variable is quantitative (overall grade); explanatory variables are quantitative (study hours, recreational spending) and binary (part-time work); = multiple regression d) Outcome variable is binary (paid part-time work – Yes/No); explanatory variable is binary (gender); = two-sample z-test of proportions, OR chi-square test of independence e) Outcome variable is quantitative (overall grade); explanatory variable is binary (gender); = two-sample t-test of independent means [also acceptable to use (9): one-way ANOVA] f) There is only one sample here and the variable is binary (Facebook user – Yes/No). Compare the estimate from the single sample with the external target; = one-sample z-test of a single proportion g) There is only one sample here and the variable is quantitative (recreational expenditure). Compare the estimate from the single sample with the external target; = one-sample t-test of a single mean h) Each respondent’s first-year data value is matched with his/her second-year data value. Hence the outcome variable is the difference between first-year and second-year overall grade, so this is a one-sample test of the differences; = matched pairs t-test i) Outcome variable is quantitative (overall grade); explanatory variable is quantitative (study hours); = linear regression j) Outcome variable is quantitative (study hours); explanatory variable is categorical (mode of travel, 4 categories); = one-way analysis of variance 3
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FE2012 A5 “Ford had a Model T; you have a t model” (i) H 0 : μ d = 0; H a : μ d ≠ 0 (ii) Output 2 (iii) Two measurements per car => dependent means (iv) (v) 0.034 (vi) There is evidence at the 5% level of a difference in mean appraisals between the two appraisers. (vii) There is – There is not b) Output 1 There is not enough evidence at the 5% level to conclude a difference between appraisers with respect to mean appraisals. c) (-263,415) Details and Comments: (i) It is also acceptable to write: H 0 : μ 1 – μ 2 = 0; or H 0 : μ 1 = μ 2 . Similarly for H a . (ii) and (iii) Observations are paired – the same car is appraised twice – so the matched pairs t-test is appropriate here. (iv) Formula for paired t-stat (v) Use the two-tailed P-value since the alternative hypothesis is two-sided.
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