Category: R

Using the dataset, Concession Data complete the following tasks in excel.
Here is a brief overview of the two tabs in the excel file.
Sales Transactions – each line on this tab represents a concession sale, a very simple sale, of one item and one single quantity, but a sale nonetheless. It contains the date, the item sold, the category and what the item was sold for.
Item Look up Table – this tab contains your look up values that you will need for your calculations. It includes your cost for each of the items, meaning what did it really cost to make the popcorn or the hot dog (not what you sold it for) and how many calories the popcorn is for example.
For your assignment, you will need to follow the below transformation steps and then complete a simple report in Word/PDF summarizing what you did.
Start with the Sales Transactions Tab, it contains some messy data that needs cleaning.Group the items and categories and identify if there are misspellings or errors. This would most easily be done by creating a pivot table. (see Pivot Tables for help.)
Hint: Since these are concession sales, I would expect sale prices to be the same, so you can make some generalizations if you see anomalies or blanks there.
Check for missing values or blanks
Are there duplicates of the groups and are they valid?
Identify data with the wrong data type.
Are any of the dates incorrect? All transactions should have taken place in January 2022
Now that you have cleaned the transactional data, you are ready to use the look up table to do a couple calculations. (See Vlookup: When and How to use it for help.)Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold. (Ex: Sold item for $5, cost of goods sold, $2.50, Profit = $2.50 or 100%)Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.
Submission InstructionsSubmit a Word/PDF file along with your excel file that shows your work. The Word/PDF file should contain the following items and a brief explanation of the steps taken to cleanse the transactional data. If you have any open questions, please include those as well.Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold.Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.

Using the dataset, Concession Data complete the following tasks in excel.
Here is a brief overview of the two tabs in the excel file.
Sales Transactions – each line on this tab represents a concession sale, a very simple sale, of one item and one single quantity, but a sale nonetheless. It contains the date, the item sold, the category and what the item was sold for.
Item Look up Table – this tab contains your look up values that you will need for your calculations. It includes your cost for each of the items, meaning what did it really cost to make the popcorn or the hot dog (not what you sold it for) and how many calories the popcorn is for example.
For your assignment, you will need to follow the below transformation steps and then complete a simple report in Word/PDF summarizing what you did.
Start with the Sales Transactions Tab, it contains some messy data that needs cleaning.Group the items and categories and identify if there are misspellings or errors. This would most easily be done by creating a pivot table. (see Pivot Tables for help.)
Hint: Since these are concession sales, I would expect sale prices to be the same, so you can make some generalizations if you see anomalies or blanks there.
Check for missing values or blanks
Are there duplicates of the groups and are they valid?
Identify data with the wrong data type.
Are any of the dates incorrect? All transactions should have taken place in January 2022
Now that you have cleaned the transactional data, you are ready to use the look up table to do a couple calculations. (See Vlookup: When and How to use it for help.)Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold. (Ex: Sold item for $5, cost of goods sold, $2.50, Profit = $2.50 or 100%)Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.
Submission InstructionsSubmit a Word/PDF file along with your excel file that shows your work. The Word/PDF file should contain the following items and a brief explanation of the steps taken to cleanse the transactional data. If you have any open questions, please include those as well.Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold.Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.

Using the dataset, Concession Data complete the following tasks in excel.
Here is a brief overview of the two tabs in the excel file.
Sales Transactions – each line on this tab represents a concession sale, a very simple sale, of one item and one single quantity, but a sale nonetheless. It contains the date, the item sold, the category and what the item was sold for.
Item Look up Table – this tab contains your look up values that you will need for your calculations. It includes your cost for each of the items, meaning what did it really cost to make the popcorn or the hot dog (not what you sold it for) and how many calories the popcorn is for example.
For your assignment, you will need to follow the below transformation steps and then complete a simple report in Word/PDF summarizing what you did.
Start with the Sales Transactions Tab, it contains some messy data that needs cleaning.Group the items and categories and identify if there are misspellings or errors. This would most easily be done by creating a pivot table. (see Pivot Tables for help.)
Hint: Since these are concession sales, I would expect sale prices to be the same, so you can make some generalizations if you see anomalies or blanks there.
Check for missing values or blanks
Are there duplicates of the groups and are they valid?
Identify data with the wrong data type.
Are any of the dates incorrect? All transactions should have taken place in January 2022
Now that you have cleaned the transactional data, you are ready to use the look up table to do a couple calculations. (See Vlookup: When and How to use it for help.)Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold. (Ex: Sold item for $5, cost of goods sold, $2.50, Profit = $2.50 or 100%)Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.
Submission InstructionsSubmit a Word/PDF file along with your excel file that shows your work. The Word/PDF file should contain the following items and a brief explanation of the steps taken to cleanse the transactional data. If you have any open questions, please include those as well.Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold.Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.

Using the dataset, Concession Data complete the following tasks in excel.
Here is a brief overview of the two tabs in the excel file.
Sales Transactions – each line on this tab represents a concession sale, a very simple sale, of one item and one single quantity, but a sale nonetheless. It contains the date, the item sold, the category and what the item was sold for.
Item Look up Table – this tab contains your look up values that you will need for your calculations. It includes your cost for each of the items, meaning what did it really cost to make the popcorn or the hot dog (not what you sold it for) and how many calories the popcorn is for example.
For your assignment, you will need to follow the below transformation steps and then complete a simple report in Word/PDF summarizing what you did.
Start with the Sales Transactions Tab, it contains some messy data that needs cleaning.Group the items and categories and identify if there are misspellings or errors. This would most easily be done by creating a pivot table. (see Pivot Tables for help.)
Hint: Since these are concession sales, I would expect sale prices to be the same, so you can make some generalizations if you see anomalies or blanks there.
Check for missing values or blanks
Are there duplicates of the groups and are they valid?
Identify data with the wrong data type.
Are any of the dates incorrect? All transactions should have taken place in January 2022
Now that you have cleaned the transactional data, you are ready to use the look up table to do a couple calculations. (See Vlookup: When and How to use it for help.)Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold. (Ex: Sold item for $5, cost of goods sold, $2.50, Profit = $2.50 or 100%)Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.
Submission InstructionsSubmit a Word/PDF file along with your excel file that shows your work. The Word/PDF file should contain the following items and a brief explanation of the steps taken to cleanse the transactional data. If you have any open questions, please include those as well.Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold.Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.

Using the dataset, Concession Data complete the following tasks in excel.
Here is a brief overview of the two tabs in the excel file.
Sales Transactions – each line on this tab represents a concession sale, a very simple sale, of one item and one single quantity, but a sale nonetheless. It contains the date, the item sold, the category and what the item was sold for.
Item Look up Table – this tab contains your look up values that you will need for your calculations. It includes your cost for each of the items, meaning what did it really cost to make the popcorn or the hot dog (not what you sold it for) and how many calories the popcorn is for example.
For your assignment, you will need to follow the below transformation steps and then complete a simple report in Word/PDF summarizing what you did.
Start with the Sales Transactions Tab, it contains some messy data that needs cleaning.Group the items and categories and identify if there are misspellings or errors. This would most easily be done by creating a pivot table. (see Pivot Tables for help.)
Hint: Since these are concession sales, I would expect sale prices to be the same, so you can make some generalizations if you see anomalies or blanks there.
Check for missing values or blanks
Are there duplicates of the groups and are they valid?
Identify data with the wrong data type.
Are any of the dates incorrect? All transactions should have taken place in January 2022
Now that you have cleaned the transactional data, you are ready to use the look up table to do a couple calculations. (See Vlookup: When and How to use it for help.) Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold. (Ex: Sold item for $5, cost of goods sold, $2.50, Profit = $2.50 or 100%)Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.
Submission InstructionsSubmit a Word/PDF file along with your excel file that shows your work. The Word/PDF file should contain the following items and a brief explanation of the steps taken to cleanse the transactional data. If you have any open questions, please include those as well.Profit – calculate the actual profit based on the cost of goods sold number. To calculate profit, you will want to take the amount you sold the item for minus the cost of goods sold. Calculate the profit per line in dollars
Calculate the profit per day in dollars
Calculate the profit in total (all sales) in dollars
Identify which items did were most profitable, which were least profitable (where you didn’t make any money!), and which (if any) broke even in dollars
Total Calories – using the look up table, do another vlookup to identify the calorie amount per transaction lineCalculate the total calories per line (Hint: should just match the calories from the look up table, this isn’t a trick)
Calculate the total calories per day
Calculate the total calories in total (all sales)
Identify which days had the most caloric content sold and which had the least.

Housing DataWork individually on this assignment. You are encouraged to collaborate on ideas and strategies pertinent to this assignment. Data for this assignment is focused on real estate transactions recorded from 1964 to 2016 and can be found in Housing.xlsx. Using your skills in statistical correlation, multiple regression, and R programming, you are interested in the following variables: Sale Price and several other possible predictors.If you worked with the Housing dataset in previous week – you are in luck, you likely have already found any issues in the dataset and made the necessary transformations. If not, you will want to take some time looking at the data with all your new skills and identifying if you have any clean up that needs to happen.
Complete the following:Explain any transformations or modifications you made to the dataset.
Create a linear regression model where “sq_ft_lot” predicts Sale Price.
Get a summary of your first model and explain your results (i.e., R2, adj. R2, etc.)
Get the residuals of your model (you can use ‘resid’ or ‘residuals’ functions) and plot them. What the does the plot tell you about your predictions?
Use a qq plot to observe your residuals. Do your residuals meet the normality assumption?
Now, create a linear regression model that uses multiple predictor variables to predict Sale Price (feel free to derive new predictors from existing ones). Explain why you think each of these variables may add explanatory value to the model.
Get a summary of your next model and explain your results.
Get the residuals of your second model (you can use ‘resid’ or ‘residuals’ functions) and plot them. What the does the plot tell you about your predictions?
Use a qq plot to observe your residuals. Do your residuals meet the normality assumption?
Compare the results (i.e., R2, adj R2, etc) between your first and second model. Does your new model show an improvement over the first? To confirm a ‘significant’ improvement between the second and first model, use ANOVA to compare them. What are the results?
After observing both models (specifically, residual normality), provide your thoughts concerning whether the model is biased or not.
Another important aspect of regression tasks is determining the accuracy of your predictions. For this section, we will look at root mean square error (RMSE), a common accuracy metric for regression models.Install the ‘Metrics’ package in R Studio
Using the first model, we will make predictions on the dataset using the predict function. An example would look like this (will vary for you based on variable names):‘preds <- predict(object = modelName, newdata = dataset)’ Use the ‘rmse’ function to get RMSE for the model (‘rmse(actual, predicted)’) What is the RMSE for the first model? Perform the same task for the second model. Provide the RMSE for the second model. Did the second model’s RMSE improve upon the first model? By how much? Submission InstructionsFor all assignments in this course, you must export the script or Markdown file to PDF. All submissions must include a PDF that includes your code and output. You are welcome to include your script or a link to GitHub or another external repo, but you must also include a PDF at a minimum. No zip files are accepted either.Answer: Upload RMarkdown file & PDF Requirements: RMarkdown and PDF | .doc file

This dataset is a collection of the COVID-19 data maintained by Our
World in Data. The names and descriptions of variables in the data set
are provided below.
iso_code : ISO 3166-1 alpha-3 – three-letter country codes
continent: Continent of the geographical location
location: Geographical location
date: Date of observation
new_cases_per_million: New confirmed cases of COVID-19 per 1,000,000 people
new_deaths_per_million: New deaths attributed to COVID-19 per 1,000,000 people
people_vaccinated_per_hundred: Total number of people who received at least one vaccine dose per 100 people in the total population
people_fully_vaccinated_per_hundred: Total number of people who received all doses prescribed by the vaccination protocol per 100 people …
median_age: Median age of the population, UN projection for 2020
gdp_per_capita: Gross domestic product at purchasing power parity (constant 2011 international dollars), most recent…
cardiovasc_death_rate: Death rate from cardiovascular disease in 2017 (annual number of deaths per 100,000 people)
diabetes_prevalence: Diabetes prevalence (% of population aged 20 to 79) in 2017
life_expectancy: Life expectancy at birth in 2019
human_development_index: A composite index measuring average achievement in three basic dimensions of human development.

Use any packaging below
install.packages(“tidyverse”)
install.packages(“broom”)
install.packages(“rddtools”)
library(tidyverse)
library(broom)
library(rddtools)

Use any packaging below
install.packages(“tidyverse”)
install.packages(“broom”)
install.packages(“rddtools”)
library(tidyverse)
library(broom)
library(rddtools)

Housing DataWork individually on this assignment. You are encouraged to collaborate on ideas and strategies pertinent to this assignment. Data for this assignment is focused on real estate transactions recorded from 1964 to 2016 and can be found in Housing.xlsx. Using your skills in statistical correlation, multiple regression, and R programming, you are interested in the following variables: Sale Price and several other possible predictors.If you worked with the Housing dataset in previous week – you are in luck, you likely have already found any issues in the dataset and made the necessary transformations. If not, you will want to take some time looking at the data with all your new skills and identifying if you have any clean up that needs to happen.
Complete the following:Explain any transformations or modifications you made to the dataset.
Create a linear regression model where “sq_ft_lot” predicts Sale Price.
Get a summary of your first model and explain your results (i.e., R2, adj. R2, etc.)
Get the residuals of your model (you can use ‘resid’ or ‘residuals’ functions) and plot them. What the does the plot tell you about your predictions?
Use a qq plot to observe your residuals. Do your residuals meet the normality assumption?
Now, create a linear regression model that uses multiple predictor variables to predict Sale Price (feel free to derive new predictors from existing ones). Explain why you think each of these variables may add explanatory value to the model.
Get a summary of your next model and explain your results.
Get the residuals of your second model (you can use ‘resid’ or ‘residuals’ functions) and plot them. What the does the plot tell you about your predictions?
Use a qq plot to observe your residuals. Do your residuals meet the normality assumption?
Compare the results (i.e., R2, adj R2, etc) between your first and second model. Does your new model show an improvement over the first? To confirm a ‘significant’ improvement between the second and first model, use ANOVA to compare them. What are the results?
After observing both models (specifically, residual normality), provide your thoughts concerning whether the model is biased or not.
Another important aspect of regression tasks is determining the accuracy of your predictions. For this section, we will look at root mean square error (RMSE), a common accuracy metric for regression models.Install the ‘Metrics’ package in R Studio
Using the first model, we will make predictions on the dataset using the predict function. An example would look like this (will vary for you based on variable names):‘preds <- predict(object = modelName, newdata = dataset)’ Use the ‘rmse’ function to get RMSE for the model (‘rmse(actual, predicted)’) What is the RMSE for the first model? Perform the same task for the second model. Provide the RMSE for the second model. Did the second model’s RMSE improve upon the first model? By how much? Submission InstructionsFor all assignments in this course, you must export the script or Markdown file to PDF. All submissions must include a PDF that includes your code and output. You are welcome to include your script or a link to GitHub or another external repo, but you must also include a PDF at a minimum. No zip files are accepted either.Answer: Upload RMarkdown file & PDF Requirements: RMarkdown and PDF | .doc file