Answer:
a to the -56th power, a to the 72nd power, and a squared.
Step-by-step explanation:
X(x+4)
(x+2)^2-4
(x+4)x
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Answer:
A) THE MEAN DIFFERENCE = 22.2 - 20 = 2.2
B) HERE WE NEED TO CALCULATE THE MARGIN OF ERROR
AS GIVEN THE VARIANCE = 384
THEREFORE STANDARD DEVIATION = (384)^(1/2) = 19.59
THE MARGIN OF ERROR = STANDARD DEVIATION / SQRT(N) = 19.59/SQRT(25) = 19.59/5 = 3.91
C) AS THE SAMPLE SIZE IS LESS THEN 30 THEREFORE WE WILL DO IT BY THE T TEST
We need to test the null H0 : µ = 20 against the TWO-sided alternative H1 : µ\neq 20, at level α = 0.05. Since n is SMALL, we will do a SMALL-sample T-test. The rejection region is T >Tα = 1.96OR T<-Tα = -1.96, using the normal table.
T= (X − µ0) /(S/√ n) = (22.2 − 20)/( 19.59/ √ 25) = 0.56 Since T = 0.56 < 1.96, H0 is ACCEPTED. Thus, there is significant evidence at 5% signifi- cance level .
Step-by-step explanation:
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We square the residuals when using the least-squares line method to find the line of best fit because we believe that huge negative residuals (i.e., points well below the line) are just as harmful as large positive residuals (i.e., points that are high above the line).
<h3>What do you mean by Residuals?</h3>
We treat both positive and negative disparities equally by squaring the residual values. We cannot discover a single straight line that concurrently minimizes all residuals. The average (squared) residual value is instead minimized.
We might also take the absolute values of the residuals rather than squaring them. Positive disparities are viewed as just as harmful as negative ones under both strategies.
To know more about the Least-Squares Line method, visit:
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