Answer Happy

The output given is for a multiple linear regression analysis carried out to identify the statistically significant predictors of weld strength of a spot weld. The predictor variables are Weld Time (x1: Time), Current (x2: Current), and Squeeze Pressure (X3: Pressure). The response variable is weld strength (y: Strength). The ANOVA for the Multiple Linear Regression Analysis is shown below: Analysis of Variance Analysis of Variance Source DF SS MS F P Regression 3 11573089 3857696 27.84 0.000 Residual Error 28 3879317 138547 Total 31 15452405 Assume a= 0.05 (Use P-Values for all Conclusions) What can you conclude from the result of your ANOVA hypothesis test? O All 3 of the predictor variables (current, time, and pressure) are statistically significant predictors of strength. o Only 1 of the predictor variables (current, time, and pressure) is a statistically significant predictor of strength. O None of the predictor variables (current, time, and pressure) are statistically significant predictors of strength. O At least 1 of the predictor variables (current, time, and pressure) is a statistically significant predictor of strength.

The output given is for a multiple linear regression analysis carried out to identify the statistically significant predictors of weld strength of a spot weld. The predictor variables are Weld Time (X1: Time), Current (x2: Current), and Squeeze Pressure (x3: Pressure). The response variable is weld strength (y: Strength). The R-Sq output for the regression model is shown here: s = 372.219 R-Sq = 74.9% wo Which of the following is the correct interpretation of the R-sq value? 25.1% of the variation or change in Y (Weld Strength) is explained by Time, Current, and Pressure. O 74.9% of the variation or change in Y (Weld Strength) is explained by Pressure. 74.9% of the variation or change in Y (Weld Strength) is explained by Time, Current, and Pressure. O 74.9% of the variation or change in Time, Current, and Pressure is explained by Y (Weld Strength).