{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Module 6 c.1 p-value for regression coefficient

# Module 6 c.1 p-value for regression coefficient -...

This preview shows pages 1–9. Sign up to view the full content.

Regress ANOVA ta Source Regression Residual Total Regressio variables Intercept BEVTOTAL Predicted BEVTOTAL 26,000 Regressi x Find x To find th The Sim r = r = 1. Decide is signific Y^ = b 0 + b 0 b 1 Y^ = b 0 + r 2  =  r 2  =  r 2  =  r 2  =

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
-hypothes p-value f P-Value = 2. Determ off the in -With the What we H 0 : H a :

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
sion Analysis r² 0.485 n 24 r 0.696 k 1 Std. Error 157.773 Dep. Var. FOODTOT able SS df MS F p-value 515,867.0970 1 515,867.0970 20.72 .0002 547,630.5280 22 24,892.2967 1,063,497.6250 23 on output confidence interval coefficients std. error t (df=22) p-value 95% lower 95% upper 1,749.2272 185.8265 9.413 3.59E-09 1,363.8465 2,134.6079 0.0326 0.0072 4.552 .0002 0.0178 0.0475 d values for: FOODTOT 95% Confidence Interval 95% Prediction Interval Predicted lower upper lower upper Leverage 2,597.418 2,530.278 2,664.558 2,263.400 2,931.437 0.042 ion Equation: 1,749.2272 tells us how much the natural gas is estimeated to be consumed when the tempe 0.0326 For each additional bevtot 0.0326 Expect an 0 should be substituted with the independent variable. 1,749.260 x he x-intercept assumes x = 0 mple Coefficient of Determination Explained Variation / Total Variation the simple linear regression model, which includes the independent variable explains  48.5% of the variability in  food the simple coefficient of r = 0.696  relationship between  food AND bev e whether or not the independent variable bevtot cantly related to the dependent variable food + b 1 x Our interpretation is that there is a fairly st
sis testing and simple linear regression output to find and interpret the for the regression coefficient. .0002 In the p-value for testing H is less than: represents the null hypothesis idea that there is no relations represents that there is a relationship and if so, should use  If the alternative hypothesis is correct then, There is the probability of being incorrect in concluding that there is mine the magnitude of the effect on the dependent variable food ndependent variable bevtot confidence interval and again, we will use the simple linear regression output. 95% Confidence Interval: 95% lower 95% upper 0.0178 0.0475 e know so far: 0.0326 0.0178 0.0475 .10, we have some evidence that H is false and H a is true. .05, we have strong evidence that H is false and H a is true. .01, we have very strong evidence that H is false and H a is true. .001, we have extremely strong evidence that H is false and H a is true Point of Estimate, B 0 0 Point of Estimate B 1 0 -The Point of Estimate B 1 : b 1  = -The 95% confidence interval for B 1  is:

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
for each additional independent variable we can expect an increase/decrease of the dependent va Dependent food Independent bevtot IS 0.0326 < OR > THAN 1? Increase Increase or Decrease? erature = 0 Increase of the food 1,749.2272 bevtot expenditures vtot trong  positive  or  negative  linear

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
ship between the variables  a 2-tailed test since either neg or pos relationship will be significat.
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}