Question

Open excel

In one column enter 8 heights for 10 year old boys (inches) and in the second column enter 8 weights for 10 year old boys (pounds).  Ten year old boys height ranges from 42 inches to 62 inches while the weight ranges from 60 to 90 pounds. You can make these up as long as they are reasonable if you do not have access to any data. We want to see if there is a correlation.

Move your mouse to put a box around the numbers.

From the insert menu select scatter or the chart that says scatter and then select the chart at the top left on the dropdown

Click on one of the points

Select Add Trendline

The default radio button is linear, keep it checked

Check display equation on chart and click on the display r-squared value

The equation is your least squares line

On the least squares line the slope is in front of the x value. Also, you can look at the slope of the scatter plot to see if the slope is positive. This will let you know whether to make the r value positive or negative when you take the square root of r^2.

If the r^2 value is say .0382 then you will click on an excel cell and type

=.0382^.5

Note the ^ key is above the 6 key

This will be your r value and you will make it negative if your slope is negative otherwise leave it positive.

If you have a different version of excel then you may want to search to see how to form a trendline. These instructions work with Office 365 and Office 2010.

Then follow these instructions:

Attach your scatter plot if possible. What did you get for your regression line? What was your r value? What did this tell you?

What would be a scenario where you might need to use this application?

Explain in a minimum of 250 words

Answer 1

i have attached the images of the work on excel sheet below.

in image number 1, you can see the table entries on the left and to the right you can see the scatter plot with individual regression lines, with the r squared value.

image 2 is just the close up of the scatter plot and trendline image.

image 2:

conclusions and explaination:

both the trend lines show positive inclinations, i.e, positive slopes depicting positive correlation.

now, this concept can be applied vastly when one wishes to study the relation between two variables, that is, when one wants to study the effect of one variable(here, height) on the other variable(here, weight). this is studied under the head "regression analysis" in statistics.

when two variables (or more) are positively correlated, i.e., if one increases, others increase too, and vice versa, the slope of the trend line or regression line is positive. on the other hand, if the variables are negatively correlated, the slope of the trend line is negative.

for example, if we are to study the relation between price of a product, and its quality, we can use this concept. naturally, the price inflates as the quality improves. but situations may sometimes be difficult to verbally understand. such complex situations can be tackled usimg the concept of regression analysis.

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