A chain restaurant operates locations in Evans, Martinez, and Augusta (2 locations), and the chain wants to know if there are differences in the mean number of lunch customers at any of their stores. Data for five days at each location is below.
Evans |
Martinez |
AugustaA |
AugustaB |
84 |
69 |
73 |
94 |
47 |
71 |
85 |
71 |
59 |
57 |
96 |
95 |
74 |
65 |
75 |
85 |
77 |
88 |
82 |
101 |
Carry out an ANOVA to test if there are any significant differences in lunch traffic between the four locations. Use ? = .05 to make your conclusion. Then, if there are potentially some differences among the four locations, carry out t- tests using a suitable corrected alpha to see which
locations (if any!) appear significantly different.
Anova: Single Factor | ||||||
SUMMARY | ||||||
Groups | Count | Sum | Average | Variance | ||
Evans | 5 | 341 | 68.2 | 223.7 | ||
Martinez | 5 | 350 | 70 | 130 | ||
AugustaA | 5 | 411 | 82.2 | 83.7 | ||
AugustaB | 5 | 446 | 89.2 | 136.2 | ||
ANOVA | ||||||
Source of Variation | SS | df | MS | F | P-value | F crit |
Between Groups | 1508.4 | 3 | 502.8 | 3.506276 | 0.039842 | 3.238872 |
Within Groups | 2294.4 | 16 | 143.4 | |||
Total | 3802.8 | 19 |
p-value = 0.0398 < alpha = 0.05
hence we reject the null hypothesis
there is sufficient evidence that there a re potentially some differences among the four locations
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