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
Y=1.5 at the midpoint of GH. To do this you add the y values of the endpoints together and divide by two ----> 5-2= 3 ----> 3/2= 1.5
Hope this helps you !!
Uhhh i think the answers A
To write the equation of a line I need slope and y intercept (0,y)
I have y intercept (0,7) of +7 as written in the equation
The equation y=-5/4x + 11/4 has a slope of -5/4
To get perpendicular slope is negated reciprocal
so take -5/4 and flip it -4/5 and change the sign (in this case negative to positive) 4/5
so the new equation is y=4/5x +7 (third one)
Scale Factor = 1:12
It means, for every in in the model, it is equivalent to 12 inches in the real.
Dimensions of the real Car = 132 * 66
So, Dimensions of the model = 132/12 * 66/12 = 11 * 5.5
In short, Your Answer would be: 11 * 5.5 cm
Hope this helps!
