Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant positive linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places.Advertising CostProfit323420527625730823921102311331229Find p value.
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant positive linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places.
| Advertising Cost | Profit |
|---|---|
| 3 | 23 |
| 4 | 20 |
| 5 | 27 |
| 6 | 25 |
| 7 | 30 |
| 8 | 23 |
| 9 | 21 |
| 10 | 23 |
| 11 | 33 |
| 12 | 29 |
Find p value.
Let r denote the linear correlation between advertising cost (x) and profit (y). The hypotheses are given below:
Null hypothesis:
H0 : r = 0
That is, the sample correlation coefficient (r) is not significantly different from zero. There is no significant positive linear relationship between advertising cost and profit.
Alternative hypothesis:
Ha : r ≠ 0
That is, the sample correlation coefficient is significantly different from zero.
There is a significant positive linear relationship between advertising cost and profit.
Degrees of freedom:
The formula for degrees of freedom is as follows:
Df = n – 2.
The number of data values given are 10, that is n = 10.
Substitute n = 10 in the degrees of freedom formula.
Df = n – 2 = 10 – 2 = 8.
The level of significance for the test is 0.05.
Sample correlation coefficient:
The value of the sample correlation coefficient (r) can be obtained using Excel formula.
Enter the values of advertising cost in columns A2:A11 in Excel.
Enter the values...
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