not installed, you’ll need to do a one-time installation from the Console Window in RStudio like this: install.packages("tidyverse") You cannot attempt to install packages in code that you submit to CodeGrade. If the openintro package is not installed
not installed, you’ll need to do a one-time installation from the Console Window in RStudio like this: install.packages("tidyverse") You cannot attempt to install packages in code that you submit to CodeGrade. If the openintro package is not installed
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
Related questions
Question
For this assignment, name your R file fastfoodStats.R
- For all questions you should load tidyverse, openintro, and lm.beta. You should not need to use any other libraries.
- If the tidyverse package is not installed, you’ll need to do a one-time installation from the Console Window in RStudio like this:
install.packages("tidyverse")
You cannot attempt to install packages in code that you submit to CodeGrade. - If the openintro package is not installed, you’ll need to do a one-time installation from the Console Window in RStudio like this:
install.packages("openintro")
You cannot attempt to install packages in code that you submit to CodeGrade.
- If the lm.beta package is not installed, you’ll need to do a one-time installation from the Console Window in RStudio like this:
packages("lm.beta")
You cannot attempt to install packages in code that you submit to CodeGrade. - Load tidyverse with:
suppressPackageStartupMessages(library(tidyverse))
- Load openintro with:
suppressPackageStartupMessages(library(openintro))
- Load lm.beta with:
suppressPackageStartupMessages(library(lm.beta))
The actual data set is called fastfood.
- Continue to use %>% for the pipe. CodeGrade does not support the new pipe.
- Round all float/dbl values to two decimal places.
- All statistics should be run with variables in the order I state
- E.g., “Run a regression predicting mileage from mpg, make, and type” would be:
lm(mileage ~ mpg + make + type...)
1. Run a regression predicting whether or not wine was ordered from temperature, bill, and pizza.
- Assign the coefficients of the summary of the model to Q3. It should look something like this:
Estimate Std. Error z value Pr(>|z|) (Intercept) [value] [value] [value] [value] temperature [value] [value] [value] [value] bill [value] [value] [value] [value] pizzas [value] [value] [value] [value] |
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