Answer:
0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Step-by-step explanation:
Given the data in the question;
sample size n = 28
slope of the least squares regression line of y on x or sample estimate = 0.0623
standard error = 0.0224
95% confidence interval
level of significance ∝ = 1 - 95% = 1 - 0.95 = 0.05
degree of freedom df = n - 2 = 28 - 2 = 26
∴ the equation will be;
⇒ sample estimate ± ( t-test) ( standard error )
⇒ sample estimate ± (
) ( standard error )
⇒ sample estimate ± (
) ( standard error )
⇒ sample estimate ± (
) ( standard error )
{ from t table; (
) = 2.055529 = 2.056
so we substitute
⇒ 0.0623 ± ( 2.056 )( 0.0224 )
Therefore, 0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Step-by-step explanation:
7h + 4 > 5 - 5h
7h + 5h > 5 - 4
12h > 1
h > 1/12
Answer:
SOWT analysis and career testing I think
Answer:

Step-by-step explanation:
3/8 + 1/4 + 1/2 - 2/3
- > 1/4 = 2/8
3/8 + 2/8 + 1/2 - 2/3
5/8 + 1/2 - 2/3
- > 1/2 = 4/8
5/8 + 4/8 - 2/3
9/8 - 2/3
- > LCM of 8,3: 24
- > 9/8 = 27/24
- > 2/3 = 16/24
27/24 - 16/24
11/24
Hope this helps you.