A soft-drink company is conducting research to select a new design for the can. A random sample of participants has been selected. Instead of a typical taste test with two different sodas, they gave each participant the same soda in two different cans. One can was predominantly red, and the other predominantly blue. The order was chosen randomly. Participants were asked to rate each drink on a scale of 1 to 10. The data are recorded below.
Rater | Red | Blue |
1 | 10 | 2 |
2 | 6 | 4 |
3 | 8 | 9 |
4 | 5 | 8 |
5 | 7 | 2 |
6 | 4 | 9 |
7 | 6 | 3 |
8 | 8 | 7 |
9 | 4 | 6 |
10 | 8 | 9 |
11 | 7 | 7 |
12 | 9 | 10 |
13 | 4 | 3 |
14 | 6 | 4 |
15 | 4 | 5 |
16 | 3 | 6 |
Does this sample indicate that there is a difference in the ratings based on can color? Test an appropriate hypothesis. Assume conditions have been met and that µd = red - blue
Hypotheses:
H0: µd=0; The mean difference of ratings is zero.
H0: µd (<, >, not equal to) 0; The mean difference of ratings is (greater than, less than, different than) zero.
Calculations: Type each value EXACTLY as they are given in StatCrunch
Mean:
Std. Err.:
DF:
T-Stat:
P-value:
Conclusion:
Since the P-value is (low, high), we (reject, fail to reject) the null hypothesis. There (is/is not) sufficient evidence to suggest that can color (increases, reduces, changes) the average rating of the soda.
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