Question
An analyst working at production plant is asked to estimate the price of a chemical that is used in their production process. The chemical can
An analyst working at production plant is asked to estimate the price of a chemical that is used in their production process. The chemical can be purchased from different suppliers. There are various attributes that quantify the quality of the particular chemical, and which may have an influence on its price. The analyst developed a linear regression model based these quality attributes in order to predict the price of the chemical. The linear regression modelling produced the following results:
Attribute | Coefficient | Std. Error | Std. Coefficient | Tolerance | p-Value |
Density | 5.383 | 2.201 | 0.549 | 0.362 | 0.015 |
Impurities | - 0.946 | 0.103 | -0.338 | 1.000 | 0.0 |
Reactive efficiency | 0.008 | 0.263 | 0.001 | 0.998 | 0.977 |
Packaged weight | -0.665 | 2.139 | -0.070 | 0.371 | 0.756 |
(Intercept) | 4516.427 | 63.806 | ? | ? | 0.0 |
- Write the regression equation for this model.
- Explain which attribute(s) do not play a statistically significant role in the above regression model at the 95% confidence level. Justify your answer.
- Explain which attribute(s) have a high likelihood of multi-collinearity in the above regression model. Justify your answer.
- The R-squared of the model was 0.242. Is this a good regression model? Justify your answer.
- Explain how you would remove the attribute(s) that are not statistically significant or have a high likelihood of multi-collinearity in the regression in a RapidMiner process.
Step by Step Solution
There are 3 Steps involved in it
Step: 1
Get Instant Access to Expert-Tailored Solutions
See step-by-step solutions with expert insights and AI powered tools for academic success
Step: 2
Step: 3
Ace Your Homework with AI
Get the answers you need in no time with our AI-driven, step-by-step assistance
Get Started