1. Introduction

This is an example markdown document, using the iris data set. This data set is built into RStudio and can be called up with

data <- iris

We can view the first 6 rows of the data with:

head(data)
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

2. About the data

The iris data set gives the measurements in centimeters of the variables sepal length and width and petal length and width, respectively, for 50 flowers from each of 3 species of iris. The species are Iris setosa, versicolor, and virginica.

3. Visualisations

The code below will create a scatterplot of Sepal.Length versus Sepal.Width for each of the three species:

library(tidyverse)
ggplot(data, aes(Sepal.Length, Sepal.Width)) +
  geom_point() +
  facet_wrap(~Species)

4. Linear Regression

The code below shows how to construct a linear regression model for Sepal.Width based on the variables within the data set:

model <- lm(Sepal.Width ~ Sepal.Length + Petal.Length + Petal.Width + Species, data)

The summary function is then used to call up the model results

summary(model)
## 
## Call:
## lm(formula = Sepal.Width ~ Sepal.Length + Petal.Length + Petal.Width + 
##     Species, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1.00102 -0.14786  0.00441  0.18544  0.69719 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)        1.65716    0.25595   6.475 1.40e-09 ***
## Sepal.Length       0.37777    0.06557   5.761 4.87e-08 ***
## Petal.Length      -0.18757    0.08349  -2.246   0.0262 *  
## Petal.Width        0.62571    0.12338   5.072 1.20e-06 ***
## Speciesversicolor -1.16029    0.19329  -6.003 1.50e-08 ***
## Speciesvirginica  -1.39825    0.27715  -5.045 1.34e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2678 on 144 degrees of freedom
## Multiple R-squared:  0.6352, Adjusted R-squared:  0.6225 
## F-statistic: 50.14 on 5 and 144 DF,  p-value: < 2.2e-16