Question

In: Math

Loss,x1,x2 372,45,162 206,55,233 175,61,232 154,66,231 136,71,231 112,71,237 55,81,224 45,86,219 221,53,203 166,60,189 164,64,210 113,68,210 82,79,196 32,81,180 228,56,200...

Loss,x1,x2
372,45,162
206,55,233
175,61,232
154,66,231
136,71,231
112,71,237
55,81,224
45,86,219
221,53,203
166,60,189
164,64,210
113,68,210
82,79,196
32,81,180
228,56,200
196,68,173
128,75,188
97,83,161
64,88,119
249,59,161
219,71,151
186,80,165
155,82,151
114,89,128
341,51,161
340,59,146
283,65,148
267,74,144
215,81,134
148,86,127

Need the code and comment in R-studio, and please explain it, thanks!

Q5.

Use your model to obtain the mean abrasion loss for rubber with hardness 71 an tensile strength 201. Round your answer to 2 decimal places.

Q6.

Use your model to obtain a 98% confidence interval for the mean abrasion loss for rubber with hardness 71 an tensile strength 201.

Enter here the Lower Bound for the confidence interval. Round your answer to 2 decimal places.

Q7.

After the scatter plots, the correlation between the variables, the summary of the model, R-squared and s, and the F-test, briefly comment on the adequacy of the model fit.

Expert Solution

R-Code and Outputs

Q5. the mean abrasion loss for rubber with hardness 71 an tensile strength 201. Round your answer to 2 decimal places is

=

Q6. The lower bound of the CI is 106.71

Q7. Here the multiple R-squared value is 0.8402 so the fit is good and also the p-value of the test = 1.767 x 10^-11 shows that the fitted regression model is significant.

milcah answered 1 year ago

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