Question: Correlation and Linear Regression ProjectRequirements and GradingProject Idea: ( 1 0 pts ) Before you can start the correlation project, you must have a project

Correlation and Linear Regression ProjectRequirements and GradingProject Idea:
(
1
0
pts
)
Before you can start the correlation project, you must have a project idea. Write a couple ofsentences that includes the following:
1
.
State your explanatory
(
independent
)
variable
(
must be a numerical variable
)
2
.
State your response
(
dependent
)
variable
(
must be a numerical variable
)
3
.
The variables above should be chosen such that you can obtain the data online
(
web sourcesmust be provided
)
.
Project Data
(
1
0
pts
)
Start working on the project early so you can spend some time in collecting data for your project.The requirements for your project data are as follows:
1
.
A minimum of
3
0
data points are required
.
2
.
A copy of your data along with the source must be attached to the project.The Main Project
(
8
0
total points
)
The main project consists of
3
parts. Each part is listed below as well as the requirements foreach part and the point allocations.Part A: Scatterplot
(
2
0
out of
8
0
points
)
Create a scatterplot of your explanatory and response variables using Microsoft Excel
(
Drawingscatterplot using Excel is attached under Project on Canvas
)
or an equivalent program that allowsyou to plot data. The scatterplot must meet the following requirements:
1
.
The correct data is plotted correctly
2
.
Appropriately label each axis of your graph
3
.
Include units for each axis
4
.
Give your graph a nice title
5
.
Display the line of best fit on the graph
.
6
.
Display the equation of the line of best fit somewhere near the line of best fit
.
7
.
The background color of the plot is white
(
no other color Correlation and Linear Regression Project Requirements and Grading Project Idea:
(
1
0
pts
)
Before you can start the correlation project, you must have a project idea. Write a couple of sentences that includes the following: State your explanatory
(
independent
)
variable
(
must be a numerical variable
)
State your response
(
dependent
)
variable
(
must be a numerical variable
)
The variables above should be chosen such that you can obtain the data online
(
web sources must be provided
)
.
Project Data
(
1
0
pts
)
Start working on the project early so you can spend some time in collecting data for your project. The requirements for your project data are as follows: A minimum of
3
0
data points are required. A copy of your data along with the source must be attached to the project. The Main Project
(
8
0
total points
)
The main project consists of
3
parts. Each part is listed below as well as the requirements for each part and the point allocations. Part A: Scatterplot
(
2
0
out of
8
0
points
)
Create a scatterplot of your explanatory and response variables using Microsoft Excel
(
Drawing scatterplot using Excel is attached under Project on Canvas
)
or an equivalent program that allows you to plot data. The scatterplot must meet the following requirements: The correct data is plotted correctly Appropriately label each axis of your graph Include units for each axis Give your graph a nice title Display the line of best fit on the graph. Display the equation of the line of best fit somewhere near the line of best fit. The background color of the plot is white
(
no other color
)
Part B: Results of Data Collection
(
4
0
out of
8
0
points
)
In this part of the main project, you are to type a report that summarizes your explanatory and response variables Below are
5
bullets that you must address. Be sure to address each bullet as a separate paragraph that contains
4
to
6
sentences each! Failure to do so will result in point deductions. Be thorough and provide detail when explaining each bullet. What are the explanatory variable, the response variable, and the reason you have chosen to designate them as such? What are you trying to find out and why? What is your hypothesis? Describe the pattern of your data displayed in part A
.
What kind of relation does your scatterplot show?
(
Clusters
?
Outliers?
)
Positive
/
negative
/
neither
?
Strong
/
weak
?
Correlation and Linear Regression Project Requirements and Grading Calculate and include the linear correlation coefficient,
,
and give an explanation of how the correlation coefficient supports your description of the scatterplot. Be sure to provide an explanation regarding what the value means. Furthermore, Calculate the coefficient of determination
2
and interpret it within the context of your data. When interpreting, be sure to use your variable names, not generic terms like
and
.
Display the least squares regression line and give an explanation of what the equation could be used for within the co

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