1. Report the estimated regression equation. 2. Conduct the F-test for model sig

Question

1. Report the estimated regression equation.

2. Conduct the F-test for model significance. Interpret your results.

3. Interpret the slope coefficient and test for significance using a t test.

a.    Use a t test to determine if the slope coefficient is significantly different
      (two-tail test) than the value 1.0 that is, test H0: b = 1 against H1: b ¹ 1.
b.    Of what importance is it to the company to know if this slope coefficient differs
       significantly from 1.0?

Be sure to include a copy of your Excel printout.

OUTPUT Multiple R R Square Standard Error Regression Statistics 0.488158492 0.238298714. 0.225165933 16.94057668 Observations 60 Significance F MS 1 5207.4053 207.405323 18.1453355 1.600 24H-5 58 286.9831381 Residual 16615.02201 21852.42733 p-value Upper 95% Lower 93.0% Upper 95.0% Coefficients Standard Error t Stat Lower 95% Intercept -0.380225176 22.72587814 -0.016730934 0.98670869 -15.8710 1339 45.11056304 -15.87101339 45.1 105630A X Variable 1 0.99708306 2.764898662

Explanation / Answer

1. The regression equation is Y = -0.380225 + 1.88099 X1

2. H0: The regression equation is not good fit to the given data

H1: The regression equation is good fit to the given data

Significance F = P-value of Regression = 0.0000075 which is < alpha 0.05, So reject H0

Thus we conclude that The regression equation is good fit to the given data

3.a)

H0: b = 1 against H1: b not = 1.

T-test Statistic t = (1.88099 - 1) / 0.44157 = 1.99513

t - critical value = 2

Here t - value < t - critical value, So we accept H0

Thus we conclude that population regresion coefficient is 1

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