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
Answer:
1: 216 selections
2: 120 selections
Step-by-step explanation:
1:
we have 6 different colors and we can choose the same color repeatedly, so for each of the 3 dogs, we have 6 possibilities, so the number of combinations is 6*6*6 = 216 selections.
2:
we have 6 different colors and we can't repeat a color, so the first collar has 6 possibilities, the second has 5 possibilities (one color was already chosen), and the third collar has 4 possibilities (two already chosen), so the number of selections is 6*5*4 = 120.
Find the mean of the first four test scores first.
(Add all numbers in set and divide by how many numbers there are)
81 + 87 + 71 + 89 = 328 / 4 = 82
Then, find the mean with the 85 added as the fifth term.
81 + 87 + 71 + 89 + 85 = 413 / 5 = 82.6
The impact that the 85 had on the mean test score was that the mean/average increased by 0.6.
The probability of multiple events happening is found by multiplying the probabilities of each event together.
So yes, 1/10 is the answer :)
