Week 7 regression and correlation
Look back to the raw data you collected in week 1.
There are 7 variables listed:
|Vehicle type/class||Year||Make||Model||Price||MPG (city)||MPG (highway)|
Choose TWO variables that you feel are correlated and explain why you feel that they are correlated.
Do you suspect the relation is positive or negative?
Which would be considered the independent variable, which the dependent variable?
Run a regression analysis in Excel and provide the results in your post along with your raw data.
Looking at the R2 value, explain what this indicates about the strength of the relation.
Then write out your Regression Equation, state if your p-value, and conclusion.
I encourage you to review the Week 7 Regression PDF at the bottom of the discussions.
This will give you a step-by-step example of how to calculate a correlation and run a Regression using Excel.
I DO NOT recommend doing this by hand.
Let Excel do the heavy lifting for you.
You can also use this PDF in the Quizzes section.
There are additional PDFs that were created to help you with the Homework, Lessons, and Tests in the Quizzes section.
I encourage you to review these ASAP!
These PDFs are also located at the bottom of the discussion.
Once you have posted your initial discussion, you must reply to at least two other learner’s post.
Each post must be a different topic.
So, you will have your initial post from one topic, your first follow-up post from a different topic, and your second follow-up post from one of the other topics.
Of course, you are more than welcome to respond to more than two learners.
Instructions: Make sure you include your data set in your initial post as well.
You must also respond to at least 2 other students.
Peer response #1 – Looking at your peer’s Excel output and the Regression Equation they wrote out, interpret the slope of their Regression Equation.
Use their Regression Equation to make a prediction and show the work for your predicted value based on your expression.
For example, if your peer used Year to predict Price, plug in a Year value into the regression equation and use it to predict the price of a vehicle.
Does this predicted Price value make sense with their data?
Peer response #2 – It is important to remember that typically a two-factor regression model cannot accurately describe the entire situation.
Look at the dependent variable that your peer chose.
Name at least 2 independent factors you would use to run a Multiple Linear Regression (MLR) and explain why you feel they are related.
Then use those factors to run a Multiple Linear Regression (MLR) on your peer’s data and see if the variables you chose are related to the dependent variable they chose.
What is your MLR equation?
Is your MLR significant?
Are any of the Independent factors significant?
What is the R2 value?
Explain and interpret this value and how it relates to the MLR.
Make sure you include your MLR Excel output as an attachment in your response post.
Initial post (250-word minimum) due: Thursday, by 11:59 p.m., ET
2 Classmate responses (100-word response each) due: Sunday, by 11:59 p.m., ET
My course tutor provides substantive solution to the discussion problem.