- Perform multiple linear regression analysis to identify which variables in the dataset predict the mpg of MechaCar prototypes
- Collect summary statistics on the pounds per square inch (PSI) of the suspension coils from the manufacturing lots
- Run t-tests to determine if the manufacturing lots are statistically different from the mean population
- Design a statistical study to compare vehicle performance of the MechaCar vehicles against vehicles from other manufacturers. For each statistical analysis, you’ll write a summary interpretation of the findings.
This consists of three technical analysis deliverables and a proposal for further statistical study.The following are:
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Linear Regression to Predict MPG
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Which variables/coefficients provided a non-random amount of variance to the mpg values in the dataset?
Answer
On this dataset, which is predicting miles per gallons, the result shows that the probability that each variables/coefficients helps to contributes a non-random amount of variance to the model, the length of the vehicle traveled and the clearance would not be enough to provide a statistical result of variance needed for the model.
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Is the slope of the linear model considered to be zero? Why or why not?
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No, the slope is not considered to be zero because the p-value on this data is less than 0.05. The p-value of the linear model is one of the factors that would determine the slope of the linear model
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Does this linear model predict mpg of MechaCar prototypes effectively? Why or why not?
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Summary Statistics on Suspension Coils
- T-Test on Suspension Coils and design a Study Comparing the MechaCar to the Competition
Contact
Email: equansah1@gmail.com
LinkedIn: https://www.linkedin.com/in/margaret-efua-quansah-596b01209
Twitter: https://twitter.com/Quansah_Maggie