This assignment picks up where the Module Two assignment left off and will use components of that assignment as a foundation.
You have submitted your initial analysis to the sales team at D.M. Pan Real Estate Company. You will continue your analysis of the provided Real Estate Data Spreadsheet spreadsheet using your selected region to complete your analysis. You may refer back to the initial report you developed in the Module Two Assignment Template to continue the work. This document and the National Summary Statistics and Graphs Real Estate Data PDF spreadsheet will support your work on the assignment.
Note: In the report you prepare for the sales team, the dependent, or response, variable (y) should be the listing price and the independent, or predictor, variable (x) should be the square feet.
Using the Module Three Assignment Template Word Document, specifically address the following:
Regression Equation: Provide the regression equation for the line of best fit using the scatterplot from the Module Two assignment.
Determine r: Determine r and what it means. (What is the relationship between the variables?)
Determine the strength of the correlation (weak, moderate, or strong).
Discuss how you determine the direction of the association between the two variables.
Is there a positive or negative association?
What do you see as the direction of the correlation?
Examine the Slope and Intercepts: Examine the slope B1
and intercept B0
.
Draw conclusions from the slope and intercept in the context of this problem.
Does the intercept make sense based on your observation of the line of best fit?
Determine the value of the land only.
Note: You can assume, when the square footage of the house is zero, that the price is the value of just the land. This happens when x=0, which is the y-intercept. Does this value make sense in context?
Determine the R-squared Coefficient: Determine the R-squared value.
Discuss what R-squared means in the context of this analysis.
Conclusions: Reflect on the Relationship: Reflect on the relationship between square feet and sales price by answering the following questions:
Is the square footage for homes in your selected region different than for homes overall in the United States?
For every 100 square feet, how much does the price go up (i.e., can you use slope to help identify price changes)?
What square footage range would the graph be best used for?
RESOURCES:
MAT 240: Applied Statistics, Module 3
In Module 3 of your course textbook, you will explore correlation, the correlation coefficient, the coefficient of determination, simple linear regression assumptions, and interpreting simple linear regression models. Consider the following questions as you read:
How can we use a regression equation to predict the behavior of home sales?
When is it not appropriate to interpret the intercept and slope?
What is the difference between the correlation coefficient, r, and the coefficient of determination, R-squared?
https://www.khanacademy.org/math/ap-statistics/bivariate-data-ap/least-squares-regression/v/regression-residual-intro
In a graph, the independent variable is represented on the horizontal axis, and the dependent variable is represented on the vertical axis. In the video, note the variable that is chosen for the vertical and horizontal axis from the given data. Also notice how the regression is interpreted based on the chosen variables as independent versus dependent. This interpretation helps explain the choice of the variables as being the independent or the dependent variable.
https://www.khanacademy.org/math/ap-statistics/bivariate-data-ap/assessing-fit-least-squares-regression/a/r-squared-intuition
It is important to interpret the results of a linear regression to fully understand its implications. The R-squared value helps to define what the relationship is between the two variables being studied. As you read this resource, notice how the results are interpreted and what conclusions are drawn from the information found in a regression analysis. Then, apply that approach to the project to give meaning to your calculations.
HELP FOR THIS ASSIGNMENT:
This week you have a continuation of the analysis you completed for Assignment 2-3. We will use the same data set you selected for Assignment 2-3 and expand on our findings. Below I’ve recorded a video that walks you through the Excel portion of the assignment. Additionally, you’ll find two files attached to this announcement:
1) My Excel work from the video; and
2) A sample report based on my data set.
You may use my report as a guide, but you should work to completing your own analysis.
https://youtu.be/tYmglw-fbcs and https://www.youtube.com/watch?v=IHS_PEgSxk4
THE VIDEO YOU CAN WATCH TO HELP
MORE HELP
This week we’ll expand on the topics of Module 2 and discuss more in-depth the concepts of linear regression. We will learn how to interpret a regression model such as:
y = 2.5x + 50
Were y might represent the a student score on a final exam and x would represent the hours a student spends studying. We’ll learn that the interpretation of slope (m = 2.5) tell us that, on average, for each additional hour of study a student does we can expect their exam grade in increase 2.5 points. The intercept here does have an interpretation (this isn’t always the case and see my future Excel videos for this!): for a student that studies for 0 hours we would expect them to score a 50 on the exam.
We’ll expand on these concepts by learning, in depth, about:
1) Linear Regression Assumptions – good introduction found HERE – and learn how to interpret a residual plot;
https://www.jmp.com/en_us/statistics-knowledge-portal/what-is-regression/simple-linear-regression-assumptions.html
2) The Linear Correlation Coefficient, R
– I have a video lecture HERE on this concept; https://www.youtube.com/watch?v=xdJyjwxdRZE&list=PLMIJSKMAjOLx30G3eJYdlGOpQ0LPKVKmx&index=18&t=570s
3) The coefficient of determination, R2
– A great video introduction can be found HERE. https://www.youtube.com/watch?v=COHye0a3W9Q
I will be following up the lectures above with another announcement showing the use of Excel for many major topics of the week!
I UPLOADED THE FILES THAT YOU NEED TO USE FOR THIS ASSIGNMENT AT THE END THEY ARE NAMED 3-3.
NOW TO HELP YOU DO THIS ASSIGNMENT THIS WAS WHAT I DID IN 2-3. I WILL UPLOAD THE FILE OF EVERYTHING I DID THE DOCUMENTS WILL HAVE 2-3 IN IT .
NEEDED BY SATURDAY
PLACE THIS ORDER OR A SIMILAR ORDER WITH RESEARCH MOLE TODAY AND GET AN AMAZING DISCOUNT
