[Solved] STAT823 Homework 3-Data Cleaning and Management

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File Name: STAT823_Homework_3_Data_Cleaning_and_Management.zip
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SKU: [Solved] STAT823 Homework 3-Data Cleaning and Management Category: Tag:
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  1. (a) Clean up the workspace using the rm() function. Use the data() function to display the built-in datasets you can access. Use the R help to learn more about the longley dataset: ?longley.
    • Print only the records in the longley dataset that are from the years 1947-1950: longley[longley$Year==1947:1950,]. attach(longley).
  • You track your commute times for two weeks and record the following (in minutes):17plot(Unemployed Year).
  • Change the type of plot to a line: plot(Unemployed Year, type =l)

16 20 24 22 15 21 15 17 22.

  • Enter these numbers into R and find the 5-number summary.
  • You find a data entry error, the number 24 should have been 18. Using R, replace the incorrect value without reentering the entire set of data and find the new 5-number summary.
  • Use R to count the number of times your commute was at least 20 minutes.
  • Use R to calculate the percent of your commutes that were less than 17 minutes.
  1. Using the maltreat.dta dataset, explore the variable ethnic using tab1(ethnic). There are spelling mistakes that need to be corrected. Correct mis-spelt names, and create a numeric, categorical variable ethncity. The Jola cleaning code for part (i) has been provided. Finish the remaining part of the code and produce the final (clean) bar chart.
    • Replace ethnic = Jola if ethnic value starts with a J.
    • Replace ethnic = Mandinka if ethnic value starts with an M
    • Replace ethnic = Serahule if ethnic value starts with an S
  • Replace ethnic = Wollof if ethnic value starts with a W
library(readstata13)maltreat <- read.dta13(data/maltreat.dta) # Original ethnic (string) variable tab1(maltreat$ethnic, col = grey)# convert it to a new factor variable ethnicity maltreat$ethnicity <- as.factor(maltreat$ethnic)# explore the levels (unclean) levels(maltreat$ethnicity)# clean up for Jolalevels(maltreat$ethnicity)[startsWith(levels(maltreat$ethnicity),J)] <- Jola

Distribution of maltreat$ethnic

Frequency

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[Solved] STAT823 Homework 3-Data Cleaning and Management[Solved] STAT823 Homework 3-Data Cleaning and Management
$25