Week_3_Quiz_2

library(tidyverse)

## Warning: package 'tidyverse' was built under R version 4.0.2

## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --

## v ggplot2 3.3.2     v purrr   0.3.4
## v tibble  3.0.3     v dplyr   1.0.2
## v tidyr   1.1.2     v stringr 1.4.0
## v readr   1.3.1     v forcats 0.5.0

## Warning: package 'tibble' was built under R version 4.0.2

## Warning: package 'tidyr' was built under R version 4.0.2

## Warning: package 'dplyr' was built under R version 4.0.2

## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(ggplot2)
library(dplyr)
library(mosaic)

## Warning: package 'mosaic' was built under R version 4.0.2

## Loading required package: lattice

## Loading required package: ggformula

## Warning: package 'ggformula' was built under R version 4.0.2

## Loading required package: ggstance

## Warning: package 'ggstance' was built under R version 4.0.2

## 
## Attaching package: 'ggstance'

## The following objects are masked from 'package:ggplot2':
## 
##     geom_errorbarh, GeomErrorbarh

## 
## New to ggformula?  Try the tutorials: 
##  learnr::run_tutorial("introduction", package = "ggformula")
##  learnr::run_tutorial("refining", package = "ggformula")

## Loading required package: mosaicData

## Loading required package: Matrix

## 
## Attaching package: 'Matrix'

## The following objects are masked from 'package:tidyr':
## 
##     expand, pack, unpack

## Registered S3 method overwritten by 'mosaic':
##   method                           from   
##   fortify.SpatialPolygonsDataFrame ggplot2

## 
## The 'mosaic' package masks several functions from core packages in order to add 
## additional features.  The original behavior of these functions should not be affected by this.
## 
## Note: If you use the Matrix package, be sure to load it BEFORE loading mosaic.
## 
## Have you tried the ggformula package for your plots?

## 
## Attaching package: 'mosaic'

## The following object is masked from 'package:Matrix':
## 
##     mean

## The following objects are masked from 'package:dplyr':
## 
##     count, do, tally

## The following object is masked from 'package:purrr':
## 
##     cross

## The following object is masked from 'package:ggplot2':
## 
##     stat

## The following objects are masked from 'package:stats':
## 
##     binom.test, cor, cor.test, cov, fivenum, IQR, median, prop.test,
##     quantile, sd, t.test, var

## The following objects are masked from 'package:base':
## 
##     max, mean, min, prod, range, sample, sum

library(openintro)

## Warning: package 'openintro' was built under R version 4.0.2

## Loading required package: airports

## Warning: package 'airports' was built under R version 4.0.2

## Loading required package: cherryblossom

## Warning: package 'cherryblossom' was built under R version 4.0.2

## Loading required package: usdata

## Warning: package 'usdata' was built under R version 4.0.2

## 
## Attaching package: 'openintro'

## The following object is masked from 'package:mosaic':
## 
##     dotPlot

## The following objects are masked from 'package:lattice':
## 
##     ethanol, lsegments

  getwd()    

## [1] "C:/Users/Jerome/Documents/Math_217"

Problem 2, Quiz 2

#soybeans <- read.csv("soybeans.csv")

low <-c(264,    200,    22, 268,    215,    241,    232,    256,    229,    288,    253,    288,    230)
mod <- c(314,   320,    310,    340,    299,    268,    345,    271,    285,    309,    337,    282,273)



plot (low, mod, main = "Scatterplot of Soybean Leaf Size under 2 Growing Conditions", xlab = "Low LIght", ylab = "Moderate Light")
fit <- lm(mod ~ low)
abline (fit)

Problem 1, Quiz 2

males <- c(373, 327,    274,    292,    274,    280,    301,    315,    285,    299, 320,   249,    313,    222,    254,    289,    300,    295,    292,    267 )

mean (males)

## [1] 291.05

median (males)

## [1] 292

sd (males)

## [1] 31.94811

summary(males)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   222.0   274.0   292.0   291.1   304.0   373.0

boxplot (males, main = "Serum Cholesterol Levels of 20 Males")

hist (males, main = "Histogram of Serum Cholesterol Levels of 20 Males", xlab = "Serum Cholesterol Levels")

males <-read.csv("males.csv")

title <- "Histogram of Serum Cholesterol Levels of 20 Males"

hist <-ggplot (males, aes(x = cholesterol)) +
 geom_histogram(bins = 100) + 
  labs (y = "Frequency", x = "Serum Cholesterol Levels")+
  ggtitle(title)
print(hist)