Exercise 1

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.3.6      ✔ purrr   0.3.4 
## ✔ tibble  3.1.8      ✔ dplyr   1.0.10
## ✔ tidyr   1.2.0      ✔ stringr 1.4.1 
## ✔ readr   2.1.2      ✔ forcats 0.5.2 
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## Loading required package: airports
## 
## Loading required package: cherryblossom
## 
## Loading required package: usdata
## Warning in data("fastfood", package + "openintro"): data set 'package +
## "openintro"' not found
## # A tibble: 6 × 17
##   restaur…¹ item  calor…² cal_fat total…³ sat_fat trans…⁴ chole…⁵ sodium total…⁶
##   <chr>     <chr>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>  <dbl>   <dbl>
## 1 Mcdonalds Arti…     380      60       7       2     0        95   1110      44
## 2 Mcdonalds Sing…     840     410      45      17     1.5     130   1580      62
## 3 Mcdonalds Doub…    1130     600      67      27     3       220   1920      63
## 4 Mcdonalds Gril…     750     280      31      10     0.5     155   1940      62
## 5 Mcdonalds Cris…     920     410      45      12     0.5     120   1980      81
## 6 Mcdonalds Big …     540     250      28      10     1        80    950      46
## # … with 7 more variables: fiber <dbl>, sugar <dbl>, protein <dbl>,
## #   vit_a <dbl>, vit_c <dbl>, calcium <dbl>, salad <chr>, and abbreviated
## #   variable names ¹​restaurant, ²​calories, ³​total_fat, ⁴​trans_fat,
## #   ⁵​cholesterol, ⁶​total_carb
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Based on the plots, the center for mcdonalds seems to be skewed to the right. Because of this I dont think we can call this a normal distribution.

Exercise 2

based on the plot, the curves seems to have close to a normal distribution.

Exercise 3

All the points deviate from the diagonal slightly. It is very similar to the plot of the real data as it has some major deviations at the top of the curve.

Exercise 4

The normal probability plot for the calories look very similar to the simulated normal data with the same type of deviations towards the top and bottom of the graph. I think we can conclude that the plots prove that the evidence is nearly normal.

Exercise 5

The calories from the Mcdonalds menu do not appear to come from a normal distribution as it deviates too far from the diagonal.

Exercise 6

The two questions I asked were would be the probability that a McDonalds item have more more than 300 calories and the probability that I will get more than one gram of trans fat in an item in Dairy Queen.

## [1] 0.7963677
## # A tibble: 1 × 1
##   percent
##     <dbl>
## 1   0.842
## [1] 0.3263255
## # A tibble: 1 × 1
##   percent
##     <dbl>
## 1   0.143

The calories in Mcdonalds greater had a closer agreement in method.

Exercise 7

The distribution from Dairy Queen seems to be closer to the normal for sodium.

Exercise 7

The most “normal” distributions seem to be either from Burger King or Arby’s.

Exercise 8

Some of the items may have the same sodium amount.

Exercise 9

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Based on the plots,, the data seems to be skewed slightly to the right which is confirmed by the histogram.