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(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
library(mosaic)
## Warning: package 'mosaic' was built under R version 4.0.2
## Loading required package: lattice
##
## Attaching package: 'lattice'
## The following objects are masked from 'package:openintro':
##
## ethanol, lsegments
## 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 object is masked from 'package:openintro':
##
## dotPlot
## 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
getwd()
## [1] "C:/Users/Jerome/Documents/Math_217"
rowan <- read.csv("rowan_data.csv")
plot (rowan$altitude, rowan$respiration, main = "Scatterplot of Rowan Data", xlab = "Altitude", ylab = "Respiration")
fit <- lm(rowan$respiration ~ rowan$altitude)
abline (fit)

soybean1 <- read.csv("soybean1.csv", header = TRUE)
plot (soybean1$low, soybean1$mod, main = "Soybean Leaf Size w/ Different Light Conditions", xlab = "Low", ylab = "Moderate")

hist (soybean1$low, main = "Histogram of Low LIght Soybean Leaf Size", xlab = "Leaf Size", ylab = "Frequency", breaks = 20)

testdata1 <- read.csv ("200918_test.csv", header = TRUE
)
testdata2 <- read.csv("200918_test2nd.csv", header = FALSE)
testdata3 <- read.csv ("200918_test3rd.csv")