Charity # Charity Total Expenses ($) Administrative Expenses (%) Fundraising Expenses (%) Program Expenses (%) 1...

Charity #	Charity	Total Expenses ($)	Administrative Expenses (%)	Fundraising Expenses (%)	Program Expenses (%)
1	American Red Cross	3352089148	3.8	3.9	92.0
2	World Vision	1208111251	4.0	7.5	88.3
3	Smithsonian Institution	1081275619	23.5	2.5	73.8
4	Food For the Poor	1049984888	0.6	2.6	96.8
5	American Cancer Society	1007342150	6.0	22.3	71.4
6	Volunteers of America	931512538	8.5	1.8	89.2
7	Dana-Farber Cancer Institute	876227147	13.1	1.5	85.3
8	AmeriCares	858665385	0.3	0.8	98.9
9	ALSAC - St. Jude Children's Research Hospital	830079269	9.6	17.0	73.5
10	City of Hope	734387170	13.4	2.9	83.0

1. Develop an estimated regression equation that could be used to predict the program expenses (%) given fundraising expenses (%)

Program Expenses % (pred) = ? + ? Fundraising Expenses (%) up to 2 decimals

Expert Solution

Firstly, try to plot a scatterplot between these two to find out the trend.

It shows the linear relationship between the two variables, hence linear regression can be applied here.

We will be applying the Linear regression model here, it can be done by using the function LINEST(y_value, x_value, TRUE, TRUE) where y_values contain values of Program Expenses here and x_values have Fundraising Expenses values.

Select 5 rows and 2 columns and then write the formula in the first cell and after that, press Shift + Ctrl + Enter.

The equation comes out to be -

program expenses = 90.9 - 0.90*Fundraising Expenses

orchestra answered 1 year ago

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