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: Tables, graphes, and equation are realted because they all have the same information but just in diffrent ways. the advantage of a table is that you can see more information and what other possblities and fill in missing spots. graphes you can fid the equation on it by counting on it. The advantage of a equation is that you can solve it and get the answer the fastets
step-by-step explanation:
Hope this helps
2x - 11 is the answer because you don’t know what x is equal to
Desert Shores is below the sea level and the difference is more than 600 feet
Answer:
The result is 
units.
Step-by-step explanation:
The coordinates for A and B:
A = (-2, 0)
B = (2, 2)
-To find the distance between A and B, you need the distance formula:
Where the first coordinate is 
and the second coordinate is 
.
-Use the coordinates A and B for the equation:
-Then, you solve the equation:
So, therefore the distance is 
units.
