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PLEASE ANSWER EACH QUESTION IN DETAIL! THANKYOU IN ADVANCE! For this assignment, you will use histograms...

PLEASE ANSWER EACH QUESTION IN DETAIL! THANKYOU IN ADVANCE!

For this assignment, you will use histograms to decide if datasets follow a normal distribution. Using the following sets of data, create a histogram for each one with your graphing calculator.

Property Taxes Car Insurance Premiums Annual Salary
2500 345 55000
3800 800 37000
5000 472 50000
3500 398 80000
3000 450 75000
4800 587 65000
4900 361 55000
2000 649 50000
5000 350 45000

Then provide a summary of 1-2 paragraphs in which you address the following:

Identify which variables had normally distributed data, based on your visual inspection of the histograms.

Identify which variables did not have normally distributed data, based on the histograms.

Identify and explain any characteristics relating to the data that could cause it to not be normally distributed. For example, were there outliers? If so, what were they? What could be done with the data to remove them?

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Answer #1

Activities RStudio ▼ Tue Jan 29, 00:43:21 RStudio File Edit Code View Plots Session Build Debug Profile Tools Help ⑧ Project(None) Untitled į#x Environment History Connections Files Plots Packages Help Viewer 1 Property.Taxes c(2508,388e,58e0,3500,3008.4880,4900,2000,5000) ← → Zoom Export G Publish 2 hist Property.Taxes) 3 Car.insu.preniun c(345,880,472,398,450,587,361,649,350) 4 hist(Car.insu.preiun) 5 annual.salary c(5509,37880,58008,80900,75000,65000,55000,50000,45000) 6 hist (annual.salary) Histogram of Car.insu.premium 300 400 500 600 700 800 7:1 Top Level) R Script Car.insu.premium Console

Activities RStudio ▼ Tue Jan 29, 00:43:15 RStudio File Edit Code View Plots Session Build Debug Profile Tools Help Project: (None) Untitled į#x Environment History Connections source on Save Run Source Files Plots Packages Help Viewer 1 Property.Taxes c(2508,388e,58e0,3500,3008.4880,4900,2000,5000) ZoomExport G Publish 2 hist Property.Taxes) 3 Car.insu.preniun c(345,880,472,398,450,587,361,649,350) 4 hist(Car.insu.preiun) 5 annual.salary c(5509,37880,58008,80900,75000,65000,55000,50000,45000) 6 hist (annual.salary) Histogram of Property.Taxes 2000 2500 3000 3500 4000 4500 5000 7:1 Top Level) R Script Property.Taxes ConsoleActivities RStudio ▼ Tue Jan 29, 00:43:24 File Edit Code View Plots Session Build Debug Profile Tools Help ⑧ Project(None) Untitled į#x Environment History Connections Files Plots Packages Help Viewer ← → 1 Property.Taxes c(2508,388e,58e0,3500,3008.4880,4900,2000,5000) Zoom Export G Publish 2 hist Property.Taxes) 3 Car.insu.preniun c(345,880,472,398,450,587,361,649,350) 4 hist(Car.insu.preiun) 5 annual.salary c(5509,37880,58008,80900,75000,65000,55000,50000,45000) 6 hist (annual.salary) Histogram of annual.salary เก 30000 40000 50000 60000 70000 80000 7:1 Top Level) R Script annual.salaryFrom the above three histogram we can clearly see form histogram of property taxes variable is not from a normal distribution,for the second variable i.e, car insurance premium it can be assume that it is came from truncated normal distribution where left side of the distribution been truncated.The third variable annual salary is not following normal distribution.

First variable has its maximum weightage on values from 4000 to 5000.so this distribution is like an discrete distribution with highest weightage on higher values.In the second variable we can see a right tail pattern and we may say the largest value 800 is an outlier for this distribution.In the third variable there is no outlier.We can detect outlier and them we can remove that high value data from the distribution and get the outlier free original distribution.

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