Answer:

Step-by-step explanation:
We can simplify the expressio using the product rule. The exponents will add up when multiplied with each other:



The answer is B

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
X=25 degrees
2x+3x+x+30 = 180
6x+30 = 180
180 - 30 = 150
6x = 150
150/6 = 25
X = 25
Answer:
6 pages
Step-by-step explanation:
3/4 = 8 = 2 = 1/2 = 3/4 / 8 = 6
This is confusing to understand but that's how I solved it.
No, 1/3 is greater than 1/6.
1/3 converts to 2/6.
2/6 > 1/6