12.41 Moviegoer_Correlation_Hypothesis

12.41 Moviegoer_Correlation_Hypothesis - . . . . . 2.85,...

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Regression Analysis r² 0.085 n 10 r -0.292 k 1 Std. Error 2.128 Dep. Var. Spent (y) ANOVA table Source SS df MS F p-value Regression 3.3727 1 3.3727 0.74 .4133 Residual 36.2396 8 4.5299 Total 39.6123 9 Regression output confidence interval variables coefficients std. error t (df=8) p-value 95% lower 95% upper std. coeff. Intercept 6.9609 2.0885 3.333 .0103 2.1449 11.7770 0.000 Age (x) -0.0530 0.0614 -0.863 .4133 -0.1946 0.0886 -0.292
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12.4 Moviegoer Spending ($) on Snacks (a) Make a scat er plot of the data. What does it suggest about the cor elation between X and Y? (b) Use Excel, MegaStat, or MINITAB to calculate the cor elation coef icient. (c) Use Excel or Appendix D to find t.05 for a two-tailed test. (d) Calculate the t test statistic. (e) Calculate the critical value of ra. (f) Can you reject ? = 0? Age X. . . . . . . . 30, 50, 34, 12, 37, 33, 36, 26, 18, 46 Spent Y.
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Unformatted text preview: . . . . . 2.85, 6.50, 1.50, 6.35, 6.20, 6.75, 3.60, 6.10, 8.35, 4.35 Age (x) Spent (y) 30 2.85 (a) Scat er Plot: 50 6.5 34 1.5 12 6.35 37 6.2 33 6.75 36 3.6 26 6.1 18 8.35 46 4.35 The scat er plot shows points randomly scat ered about the regression line. This means the amount spent and age of the moviegoer are poorly correlated. (b) Correlation coef icient is R = -0.2918 This value is very low and confirms the poor correlation between age of the moviegoer and the amount spent. (c) t0.05 = -2.306004 (d) t- score = -0.863 (e) Critical r = -0.632 [Using the Table from ht p:/ www.gifted.uconn.edu/siegle/research/correlation/corrchrt.htm] (f) No, we fail to reject Ho: r = 0, There is no suf icient evidence that the correlation is significant. 10 15 20 25 30 35 40 45 50 55 1 2 3 4 5 6 7 8 9 f(x) = -0.0529793609x + 6.9609354194 R = 0.085141998 Age Spent...
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12.41 Moviegoer_Correlation_Hypothesis - . . . . . 2.85,...

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