# Linear Regressions

*label*Mathematics

*timer*Asked: Sep 6th, 2017

*account_balance_wallet*$9.99

### Question Description

- Choose any Excel Discussion dataset. Include the name of the dataset. From that dataset, select any two quantitative variables that you suspect will be related (such as age and height for example). What is the name of the dataset you have chosen? Which two variables did you choose?
- Next, using Excel, calculate the relationship (r value) between the two variables. Recall that the Excel “formula” for correlation is “=CORREL.” What is the r value for the two variables that you have chosen? Is it positive or negative? Is it strong, medium, or weak? Note that it is best to have an r value that is medium or strong. It is recommended that you try a few different variables until you find two variables with an r value between .5 and 1 (or between -.5 and -1).
- Next, use Excel to create a scatterplot for the two variables. You decide which variable will be dependent (y) and which will be independent (x). On the scatterplot, include the “trendline” and the “equation for the line” using Excel options. Attach your scatterplot to your post.
- Finally, using the equation of the line that you generated above, plug in any reasonable value for x (your chosen independent variable) and solve the equation for y (your chosen dependent variable). It is up to you to determine which of your two variables is x and which is y. What prediction do you get? Show all your work. In other words, type out the equation, plug in a value for x, and show your solution for y.

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## Tutor Answer

Here is my answer :)

Linear Regressions: Female Health Data

Linear Regressions: Female Health Data

1. Choose any Excel Discussion dataset. Include the name of the dataset. From that

dataset, select any two quantitative variables that you suspect will be related (such

as age and height for example). What is the name of the dataset you have chosen?

Which two variables did you choose?

The name of the dataset that was chosen is “femalehealthdata_1” and the two variables

which were chosen are “Weight” and “Waist”.

2. Next, using Excel, calculate the relationship (r value) between the two variables.

Recall that the Excel “formula” for correlation is “=CORREL.” What is the r value

for the two variables that you have chosen? Is it positive or negative? Is it strong,

medium, or weak? Note that it is best to have an r value that is medium or strong. It

is recommended that you try a few different variables until you find two variables

with an r value between .5 and 1 (or between -.5 and -1).

Using Excel to calculate the relationship of r value between the two variables “Weight” and

“Waist” was obtained that r is equal to 0.921. We can see that r = 0.921 is a positive value

and it is strong uphill linear relationship because it is between 0.7 and 1.0.

Page 1 to 3

Linear Regressions: Female Health Data

3. Next, use Excel to create a scatterplot for the two variables. You decide which

variable will be dependent (y) and which will be independent (x). On the scatterplot,

include the “trendline...

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