In: Math
A large advertising firm specializes in creating television commercials for children’s products. The firm wants to design a study to investigate factors that may affect the lengths of time a commercial is able to hold a child’s attention. A preliminary study determines that two factors that may be important are the age of the child and the type of product being advertised. The firm wants to determine whether there were large differences in the mean length of time that the commercial is able to hold the child’s attention depending on these two factors. If there proves to be a difference, the firm would then attempt to determine new types of commercials depending on the product and targeted age group. Three age groups are used: A1: 5-6 years, A2: 7-8 years, and A3: 9-10 years. The types of products selected are P1: Breakfast cereals and P2: Video games. The data are below:
A1 |
A2 |
A3 |
|
P1 |
19 |
19 |
37 |
36 |
35 |
6 |
|
40 |
22 |
28 |
|
30 |
28 |
4 |
|
4 |
1 |
32 |
|
10 |
27 |
16 |
|
30 |
27 |
8 |
|
5 |
16 |
41 |
|
24 |
3 |
29 |
|
21 |
18 |
18 |
|
P2 |
39 |
30 |
51 |
18 |
47 |
52 |
|
32 |
6 |
43 |
|
22 |
27 |
48 |
|
16 |
44 |
39 |
|
2 |
26 |
33 |
|
36 |
33 |
56 |
|
43 |
48 |
43 |
|
7 |
23 |
40 |
|
16 |
21 |
51a. |
a. Create a two-way ANOVA table in Excel.
b. Summarize your findings.
Here we have data:
A1 | A2 | A3 | |
P1 | 19 | 19 | 37 |
P1 | 36 | 35 | 6 |
P1 | 40 | 22 | 28 |
P1 | 30 | 28 | 4 |
P1 | 4 | 1 | 32 |
P1 | 10 | 27 | 16 |
P1 | 30 | 27 | 8 |
P1 | 5 | 16 | 41 |
P1 | 24 | 3 | 29 |
P1 | 21 | 18 | 18 |
P2 | 39 | 30 | 51 |
P2 | 18 | 47 | 52 |
P2 | 32 | 6 | 43 |
P2 | 22 | 27 | 48 |
P2 | 16 | 44 | 39 |
P2 | 2 | 26 | 33 |
P2 | 36 | 33 | 56 |
P2 | 43 | 48 | 43 |
P2 | 7 | 23 | 40 |
P2 | 16 | 21 | 51 |
Excel output;
Anova: Two-Factor With Replication | ||||||
SUMMARY | A1 | A2 | A3 | Total | ||
P1 | ||||||
Count | 10 | 10 | 10 | 30 | ||
Sum | 219 | 196 | 219 | 634 | ||
Average | 21.9 | 19.6 | 21.9 | 21.13333 | ||
Variance | 157.6556 | 117.8222 | 177.6556 | 141.8437 | ||
P2 | ||||||
Count | 10 | 10 | 10 | 30 | ||
Sum | 231 | 305 | 456 | 992 | ||
Average | 23.1 | 30.5 | 45.6 | 33.06667 | ||
Variance | 191.8778 | 171.8333 | 51.15556 | 219.4437 | ||
Total | ||||||
Count | 20 | 20 | 20 | |||
Sum | 450 | 501 | 675 | |||
Average | 22.5 | 25.05 | 33.75 | |||
Variance | 165.9474 | 168.4711 | 256.1974 | |||
ANOVA | ||||||
Source of Variation | SS | df | MS | F | P-value | F crit |
Sample | 2136.067 | 1 | 2136.067 | 14.76544 | 0.000323 | 4.019541 |
Columns | 1391.7 | 2 | 695.85 | 4.810023 | 0.011956 | 3.168246 |
Interaction | 1273.633 | 2 | 636.8167 | 4.401959 | 0.016943 | 3.168246 |
Within | 7812 | 54 | 144.6667 | |||
Total | 12613.4 | 59 |
Here we have sufficient evidence to reject the null hypotheses because F-observed value (14.76544) is grater than F-critical value (4.019541) so, it is in the rejection region.
Conclusion: we can say that difference in the mean value.