Consider the data set below.
xx | 55 | 22 | 66 | 33 | 22 | 77 |
yy | 99 | 22 | 99 | 88 | 33 | 66 |
For a hypothesis test, where H0:β1=0H0:β1=0 and H1:β1≠0H1:β1≠0, and
using α=0.01α=0.01, give the following:
(a) The test statistic
t=t=
(b) The degree of freedom
df=df=
(c) The rejection region
|t|>|t|>
The final conclustion is
A. There is not sufficient evidence to reject the
null hypothesis that β1=0β1=0.
B. We can reject the null hypothesis that β1=0β1=0
and accept that β1≠0β1≠0.
The statistic software output for this problem is :
Simple linear regression results:
Dependent Variable: y
Independent Variable: x
y = 2.3649635 + 0.91240876 x
Sample size: 6
R (correlation coefficient) = 0.63708381
R-sq = 0.40587578
Estimate of error standard deviation: 2.6374617
Parameter estimates:
Parameter | Estimate | Std. Err. | Alternative | DF | T-Stat | P-value |
---|---|---|---|---|---|---|
Intercept | 2.3649635 | 2.5393803 | ≠ 0 | 4 | 0.93131522 | 0.4044 |
Slope | 0.91240876 | 0.55195225 | ≠ 0 | 4 | 1.6530574 | 0.1737 |
(a) The test statistic
t = 1.653
(b) The degree of freedom
df = 4
(c) The rejection region
|t| > 4.604
(d)
A. There is not sufficient evidence to reject the null hypothesis that β1=0
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