ASAP in R please provide the code for the following test for independence using the diamond data set: a. Load the diamond data set b. Create separate histograms for the price and carats. Choose categories/ranges for each of these columns of data based on your histograms; there should be between 3 and 5 categories for each. c. Add columns to the diamond data set that has the category for the price and the carat. It is recommened to do steps one at a time and use the mutate function to handle the cases. An example that creates a new column named PriceGroup that has two categories/bins is given below. diamond2 <- diamond2 %>% mutate(PriceGroup = case_when(price <= 400 ~ "Low Price", price > 400 ~ "High Price"))
ASAP in R please provide the code for the following test for independence using the diamond data set: a. Load the diamond data set b. Create separate histograms for the price and carats. Choose categories/ranges for each of these columns of data based on your histograms; there should be between 3 and 5 categories for each. c. Add columns to the diamond data set that has the category for the price and the carat. It is recommened to do steps one at a time and use the mutate function to handle the cases. An example that creates a new column named PriceGroup that has two categories/bins is given below. diamond2 <- diamond2 %>% mutate(PriceGroup = case_when(price <= 400 ~ "Low Price", price > 400 ~ "High Price"))
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
ASAP
in R please provide the code for the following test for independence using the diamond data set:
a. Load the diamond data set
b. Create separate histograms for the price and carats. Choose categories/ranges for each of these columns of data based on your histograms; there should be between 3 and 5 categories for each.
c. Add columns to the diamond data set that has the category for the price and the carat. It is recommened to do steps one at a time and use the mutate function to handle the cases. An example that creates a new column named PriceGroup that has two categories/bins is given below.
diamond2 <- diamond2 %>% mutate(PriceGroup =
case_when(price <= 400 ~ "Low Price",
price > 400 ~ "High Price"))
d. Create a new data frame that has the counts of the data by price and carat category using the table function.
e. Conduct the chi squared independence test to determine if the price and carat of a diamond are independent. State the hypothesis, conclusion, and justification.
f. From the results of the test, extract the expected number of results in each category pair (carat-price). Include the table.
b. Create separate histograms for the price and carats. Choose categories/ranges for each of these columns of data based on your histograms; there should be between 3 and 5 categories for each.
c. Add columns to the diamond data set that has the category for the price and the carat. It is recommened to do steps one at a time and use the mutate function to handle the cases. An example that creates a new column named PriceGroup that has two categories/bins is given below.
diamond2 <- diamond2 %>% mutate(PriceGroup =
case_when(price <= 400 ~ "Low Price",
price > 400 ~ "High Price"))
d. Create a new data frame that has the counts of the data by price and carat category using the table function.
e. Conduct the chi squared independence test to determine if the price and carat of a diamond are independent. State the hypothesis, conclusion, and justification.
f. From the results of the test, extract the expected number of results in each category pair (carat-price). Include the table.
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