Please Use Minitab for the problem and provide screenshot and file with a detailed explanation,

The values represent:

y = the thrust of a jet engine

x1 = primary speed of rotation

x2 = secondary speed of rotation

x3 = fuel flow rate

x4 = pressure

x5 = exhaust temperature

x6 = ambient temperature at time of test

y	x1	x2	x3	x4	x5	x6
4540	2140	20640	30250	205	1732	99
4315	2016	20280	30010	195	1697	100
4095	1905	19860	29780	184	1662	97
3650	1675	18980	29330	164	1598	97
3200	1474	18100	28960	144	1541	97
4833	2239	20740	30083	215	1709	87
4617	2120	20305	29831	206	1669	87
4340	1990	19961	29604	195	1640	87
3820	1702	18916	29088	171	1572	85
3368	1487	18012	28675	149	1522	85
4445	2107	20520	30120	195	1740	101
4188	1973	20130	29920	190	1711	100
3981	1864	19780	29720	180	1682	100
3622	1674	19020	29370	161	1630	100
3125	1440	18030	28940	139	1572	101
4560	2165	20680	30160	208	1704	98
4340	2048	20340	29960	199	1679	96
4115	1916	19860	29710	187	1642	94
3630	1658	18950	29250	164	1576	94
3210	1489	18700	28890	145	1528	94
4330	2062	20500	30190	193	1748	101
4119	1929	20050	29960	183	1713	100
3891	1815	19680	29770	173	1684	100
3467	1595	18890	29360	153	1624	99
3045	1400	17870	28960	134	1569	100
4411	2047	20540	30160	193	1746	99
4203	1935	20160	29940	184	1714	99
3968	1807	19750	29760	173	1679	99
3531	1591	18890	29350	153	1621	99
3074	1388	17870	28910	133	1561	99
4350	2071	20460	30180	198	1729	102
4128	1944	20010	29940	186	1692	101
3940	1830	19640	29750	178	1667	101
3480	1612	18710	29360	156	1609	101
3064	1410	17780	28900	136	1552	101
4402	2066	20520	30170	197	1758	100
4180	1954	20150	29950	188	1729	99
3973	1835	19750	29740	178	1690	99
3530	1616	18850	29320	156	1616	99
3080	1407	17910	28910	137	1569	100

8. Summary of data and regression model a. Provide descriptive statistics (mean, median, standard deviation, etc.) and a box plot for the following variables from the table: y (thrust of a jet-turbine engine) x1 (primary speed of rotation).

Provide an interpretation of these statistics and the plots.

b. Fit a multiple linear regression model using x1 (primary speed of rotation), x3 (fuel flow rate), x4 (pressure), and x5 (exhaust temperature) as the regressors. Note: Use this regression model for answering the remaining questions in this part of the report; x2 and x6 will be ignored throughout.

9. Analysis of regression a. Test for significance of regression in part (b). using = 0.05. Find the P-value for this test. Explain the results of your test.

b. Find the t-test statistic for each regressor. Using = 0.05, explain carefully the conclusion you can draw from these statistics.

c. Report R2 and the adjusted R2 for this model and explain what these tell you about the model.

10. Analysis of residuals a. Construct a normal probability plot of the residuals and interpret this graph.

b. Plot the residuals versus the fits (the estimated values of y). Are there any indications of inequality of variance or nonlinearity?

c. Plot the residuals versus x3. Is there any indication of nonlinearity?

11. Prediction a. Predict the thrust of an engine for which x1= 1950, x3 = 28900, x4 = 170, and x5 = 1589.

b. If you construct a 99% prediction interval for point estimate in part (i) would you expect it to be larger or smaller than a 95% prediction interval? Why? (No calculation is required.)

12. Future Testing Further experiments are needed to better understand engine thrust for the turbine engine project. Explain how a carefully designed experiment can produce more useful results. (Note: this question is about collecting future data and not additional analysis of the data that has already been collected.)