Stat 50 Midterm Exam

For questions 1 to 4 refer to the data “Dataques1to4.”

Question 1. Provide the same output below of the variable “AveFK” given the following interval:

1.00-1.49 Very Poor

1.50-2.49 Below Average

2.50-3.49 Average

3.50-4.49 Above average

4.50-5.00 Excellent

## `summarise()` has grouped output by 'School'. You can override using the
## `.groups` argument.

Question 2. Provide the same output below of the variable “AveSC” given the following interval:

1.00-1.49 Very Poor

1.50-2.49 Below Average

2.50-3.49 Average

3.50-4.49 Above average

4.50-5.00 Excellent

## `summarise()` has grouped output by 'School'. You can override using the
## `.groups` argument.

Question 3. Provide the same output below of the variable “AvePI” given the following interval:

1.00-1.49 Very Poor

1.50-2.49 Below Average

2.50-3.49 Average

3.50-4.49 Above average

4.50-5.00 Excellent

## `summarise()` has grouped output by 'School'. You can override using the
## `.groups` argument.

Question 4. Provide the same output below of the variable “AveRR” given the following interval:

1.00-1.49 Very Poor

1.50-2.49 Below Average

2.50-3.49 Average

3.50-4.49 Above average

4.50-5.00 Excellent

## `summarise()` has grouped output by 'School'. You can override using the
## `.groups` argument.

Using the data “Dataquest5to11” for questoins 5 to 10.

## New names:
## • `` -> `...6`
## • `` -> `...7`
## • `` -> `...8`
## • `` -> `...9`
## • `` -> `...10`
## • `` -> `...11`
## • `` -> `...12`

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.3.6     ✔ purrr   0.3.4
## ✔ tibble  3.1.8     ✔ stringr 1.4.0
## ✔ tidyr   1.2.0     ✔ forcats 0.5.2
## ✔ readr   2.1.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ rstatix::filter() masks dplyr::filter(), stats::filter()
## ✖ dplyr::lag()      masks stats::lag()

Create a new variable named “Phase” with the variables “Adlay with wash”, “Adlay with milk”, and “Adlay with milk and molasses” as the responses. With this, make a variable “CFUcount” for the responses of the variable “Phase.” Refer the output below

Question 5. Provide the same output below:

Question 6. Provide the same output below:

Question 7. Provide the same output below:

Question 8. Provide the same output below:

Question 9. Provide the same output below:

Question 10. Generate two graphical presentations of the provided data.