Discussion2

Iris Data Set

data(iris)
str(iris)

## 'data.frame':    150 obs. of  5 variables:
##  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
##  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
##  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
##  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

library(psych)

describe(iris)

##              vars   n mean   sd median trimmed  mad min max range  skew
## Sepal.Length    1 150 5.84 0.83   5.80    5.81 1.04 4.3 7.9   3.6  0.31
## Sepal.Width     2 150 3.06 0.44   3.00    3.04 0.44 2.0 4.4   2.4  0.31
## Petal.Length    3 150 3.76 1.77   4.35    3.76 1.85 1.0 6.9   5.9 -0.27
## Petal.Width     4 150 1.20 0.76   1.30    1.18 1.04 0.1 2.5   2.4 -0.10
## Species*        5 150 2.00 0.82   2.00    2.00 1.48 1.0 3.0   2.0  0.00
##              kurtosis   se
## Sepal.Length    -0.61 0.07
## Sepal.Width      0.14 0.04
## Petal.Length    -1.42 0.14
## Petal.Width     -1.36 0.06
## Species*        -1.52 0.07

plot(x = iris$Sepal.Width, y = iris$Sepal.Length,
     xlab = 'Sepal Width', ylab = 'Sepal Length',
     col = iris$Species)

plot(x = iris$Petal.Width, y = iris$Petal.Length,
     xlab = 'Petal Width', ylab = 'Petal Length',
     col = iris$Species)

Questions:

1. There are 150 total cases in the data. However, there is 50 cases for each specific species of iris flower; which there were 3 of.

2. 5 numeric variables in the data

Discrete: ‘Observation Number’: measuring occurrences and has counted and finite value.

Continuous: Sepal.Width, Sepal.Length, Petal.Width, Petal.Length: these are continuous because these variables are on a continuous scale and have decimal places.

3. There is one categorical variable present in the dataset; Species. The Species variable has 3 categories (setosa, versicolor, virginica).

BOD Data Set

data(BOD)
plot(y = BOD$demand, x = BOD$Time, type = 'l',
     xlab = 'Time', ylab = 'Oxygen Demand')

describe(BOD)

##        vars n  mean   sd median trimmed  mad min  max range  skew kurtosis   se
## Time      1 6  3.67 2.16    3.5    3.67 2.22 1.0  7.0   6.0  0.26    -1.58 0.88
## demand    2 6 14.83 4.63   15.8   14.83 5.34 8.3 19.8  11.5 -0.29    -1.86 1.89

The dataset BOD shows Biochemical Oxygen Demand with ‘Time’ and ‘Oxygen Demand’ as the variables. This is a time series because it is tracking one entity (biochemical oxygen demand) over time.