Question

need step by step for MINITAB please

Problem 1. Consider the GASTURBINE data set and corresponding output from Minitab. Use the complete data set in your analysis. The first 10 observations are given for illustrative purposes. Complete parts a) through g) below.

ENGINE	SHAFTS	RPM	CPRATIO	INLET-TEMP	EXH-TEMP	AIRFLOW	POWER	HEATRATE
Traditional	1	27245	9.2	1134	602	7	1630	14622
Traditional	1	14000	12.2	950	446	15	2726	13196
Traditional	1	17384	14.8	1149	537	20	5247	11948
Traditional	1	11085	11.8	1024	478	27	6726	11289
Traditional	1	14045	13.2	1149	553	29	7726	11964
Traditional	1	6211	15.7	1172	517	176	52600	10526
Traditional	1	6210	17.4	1177	510	193	57500	10387
Traditional	1	3600	13.5	1146	503	315	89600	10592
Traditional	1	3000	15.1	1146	524	375	113700	10460
Traditional	1	3000	15	1171	525	514	164300	10086

Regression Analysis: HEATRATE versus RPM, CPRATIO, …

The regression equation is

HEATRATE = 14314 + 0.0806 RPM - 6.8 CPRATIO - 9.51 INLET-TEMP + 14.2 EXH-TEMP

           - 2.55 AIRFLOW + 0.00426 POWER

Predictor       Coef   SE Coef      T      P

Constant       14314      1112 12.87 0.000

RPM          0.08058   0.01611   5.00 0.000

CPRATIO        -6.78     30.38 -0.22 0.824

INLET-TEMP    -9.507     1.529 -6.22 0.000

EXH-TEMP      14.155     3.469   4.08 0.000

AIRFLOW       -2.553     1.746 -1.46 0.149

POWER       0.004257 0.004217   1.01 0.317

S = 458.757   R-Sq = 92.5%   R-Sq(adj) = 91.7%

Analysis of Variance

Source          DF         SS        MS       F      P

Regression       6 155269735 25878289 122.96 0.000

Residual Error 60   12627473    210458

Total           66 167897208

1. Write a first-order model in general form for the model that includes RPM, CPRATIO, INLET-TEMP, EXH-TEMP, AIRFLOW, and POWER to predict HEATRATE.
   
2. Use Minitab to compose regression equation for HEATRATE based on RPM, CPRATIO, INLET-TEMP, EXH-TEMP, AIRFLOW, and POWER. Paste the output here:

3. Write out the least squares prediction equation for the model that was fit above.

4. Calculate and give an interpretation of the coefficients based on a one-unit change in each x_i. Calculate and give an interpretation of the effect on HEATRATE based on a 1-unit change in AIRFLOW together with a 210-unit change in POWER.

5. Interpret the overall model F-test. State the appropriate hypothesis test and associated numerator and denominator degrees of freedom used for this test as well as the critical value that the test statistic is compared to. State the conclusion you would make regarding the null hypothesis. Specifically, would you reject or fail to reject the null hypothesis, and what does this conclusion means about the model parameters? Does this tell us anything about the significance of the individual predictors? Why or why not?

                            

6. Report and interpret the model R².

7. Which predictors are significant in the model? Report the appropriate hypothesis test and formal conclusion you would make regarding RPM and CPRATIO. In your conclusion, state their p-values and test statistics. Would you suggest removing all non-significant predictors at once and refitting the model? Why or why not?

Answer 1