Question

X	Y
1,000	500
3,000	400
7,000	750
12,000	1,000
15,500	1,200
17,000	1,000
17,500	1,800
21,000	2000
22,800	2,200
23,000	3,000

g. Does it appear that a line is the best way to fit the data? Why or why not?

h. Are there any outliers in the data?

i. Based on these results, what would be the probate fees and taxes for an estate that does not have any assets?

j. What is the slope of the least-squares (best-fit) line? Interpret the slope

Answer 1

g. For this, we can try scatterplot:

there definitely appears to be a straight line positive relationship.

h.

For X,

there are no outliers.

For Y,

there are outliers.

Collectively, in scatterplot, point

23,000

3,000

is little out but cannot be considered outlier.

i. Running linear regression in excel, we get output:

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.89044
R Square	0.792883
Adjusted R Square	0.766993
Standard Error	404.191
Observations	10
ANOVA
	df	SS	MS	F	Significance F
Regression	1	5003287	5003287	30.62543	0.000551
Residual	8	1306963	163370.4
Total	9	6310250

	Coefficients	Standard Error	t Stat	P-value
Intercept	79.72161	268.2703	0.297169	0.773908
X Variable 1	0.093368	0.016872	5.534024	0.000551

So, regression : Y = 79.72 + 0.09*X

or for the people who do not have any assets, the probate fees and taxes will be $79.72 since X = 0.

j. slope = 0.093

which mean for a unit increase in assets there will be 0.093 units of increase in probate fees and taxes.

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