Part 1
| t-Test: Paired Two Sample for Means | ||
|
Men |
Women |
|
| Mean |
1.701219512 |
1.531707317 |
| Variance |
0.271685976 |
0.255594512 |
| Observations |
41 |
41 |
| Pearson Correlation |
0.200500447 |
|
| Hypothesized Mean Difference |
0 |
|
| df |
40 |
|
| t Stat |
1.671619968 |
|
| P(T<=t) one-tail |
0.051202872 |
|
| t Critical one-tail |
1.683851013 |
|
| P(T<=t) two-tail |
0.102405745 |
|
| t Critical two-tail |
2.02107539 |
|
Figure 1. t-value outputs
| SUMMARY OUTPUT | ||||||||
|
Regression Statistics |
||||||||
| Multiple R |
0.932182561 |
|||||||
| R Square |
0.868964328 |
|||||||
| Adjusted R Square |
0.843323302 |
|||||||
| Standard Error |
0.657143925 |
|||||||
| Observations |
40 |
|||||||
| ANOVA | ||||||||
|
df |
SS |
MS |
F |
Significance F |
||||
| Regression |
1 |
111.6858126 |
111.6858126 |
258.62888 |
1.5178E-18 |
|||
| Residual |
39 |
16.84168737 |
0.431838138 |
|||||
| Total |
40 |
128.5275 |
||||||
|
Coefficients |
Standard Error |
t Stat |
P-value |
Lower 95% |
Upper 95% |
Lower 95.0% |
Upper 95.0% |
|
| Intercept |
0 |
#N/A |
#N/A |
#N/A |
#N/A |
#N/A |
#N/A |
#N/A |
|
2 |
1.044280623 |
0.06493498 |
16.08194258 |
8.349E-19 |
0.91293723 |
1.17562402 |
0.912937228 |
1.175624018 |
Delegate your assignment to our experts and they will do the rest.
Figure 2. Regression analysis outputs
From the Excel outputs:
The two-tailed t-value is 0.102405745, the degree of freedom is 40, the significance value is 0.2005 and the Standard Error is 0.671439.
Part 2
Introduction
An agency that undertakes advertising of its products is interested in understanding whether there is a relationship in the rate of viewership of different gender. The data pertaining to 41 respondents were recorded in an Excel file after which regression and t-test analyses were performed to derive statistical evidences that provide an understanding of the relationship between the variables.
Hypotheses
The null hypothesis was:
H0: There is no relationship between the rates of viewership of TV ads among men to that of women.
The alternative hypothesis was:
H1: There is a relationship between the rates of viewership of TV ads among men to that of women.
From the statistical data presented, the relationship between the rates of viewership among men and that of women is greater than the significance level of 0.05; therefore we reject the alternative hypothesis and fail to reject the null hypothesis.
Conclusion from the Analysis
From the analysis, it is concluded that the probability of getting viewership of 0.1024 when a sample from the population is taken is 0.2005 while the impact of other factors that are not measured but are likely to impact the relationship between the two variables is 0.6751.
Implications of the findings to the Advertising Agency
Since the findings shows that there is no statistical relationship between the rate of viewership among men and women, it implies that the advertising should be done with the focus on the needs of either gender without greater focus on a specific gender ( Bagwell, 2007) .
Conclusion
This study involved the analysis of the rate of viewership of an advertising program among men and women in which a survey was conducted among 41 participants. It was established that the relationship between the variables was greater than the significance value of 0.05, thus the alternative hypothesis was rejected while the null hypothesis was not rejected.
References
Bagwell, K. (2007). The economic analysis of advertising. Handbook of industrial organization , 3 , 1701-1844.
