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:
Step-by-step explanation:
We know that 
Also , 
So ,
Answer:
there is nothing to select. u need to provide more info
Answer:
<u>The correct answer is C. It is the original amount of money the bank loans the borrower.</u>
Step-by-step explanation:
Let's recall that are five basic elements for calculating the payment of a loan:
1. The principal. How much money you borrow.
2. The interest rate. How much money you will pay in addition to the principal.
3. The period of time. How long will it takes you to pay the loan.
4. The frequency of payment. Will you pay every month?, every quarter?, every year or maybe every two weeks?
5. Additional payments. When you have additional income seasonally and you want to lower either the period of time or the interests to pay.
