3.6 Computer Examples

This section summarizes how to make histograms and scatter plots with the computer software.

Histograms

from sie import *

Load a sample data set, and select only the Male data...

data=load_data('data/survey.csv')
male_data=data[data['Sex']=='Male']

select only the height data, and drop the missing data (na)...

male_height=male_data['Height'].dropna()

make the histogram

hist(male_height,bins=20)
xlabel('Height [cm]')
ylabel('Number of People')

Show expected output

<matplotlib.text.Text at 0x1085728d0>

Histogram of the class height data in centimeters produced by the sample code: bars from about 155 to 200 cm with the tallest bar of 16 people just above 180 cm.

Scatter Plot

from sie import *

Load a sample data set, and select only the Male data...

data=load_data('data/survey.csv')
male_data=data[data['Sex']=='Male']

select only the height and the width of writing hand data, and drop the missing data (na)...

subdata=male_data[['Height','Wr.Hnd']].dropna()
height=subdata['Height']
wr_hand=subdata['Wr.Hnd']

plot the data

plot(height,wr_hand,'o')
ylabel('Writing Hand Span [cm]')
xlabel('Height [cm]')

Show expected output

<matplotlib.text.Text at 0x1085774d0>

Scatter plot from the sample code of writing hand span against height for the class data: a broad cloud of points between 150-200 cm height and 16-23 cm span, drifting upward to the right.

Adapted from Statistical Inference for Everyone, by Brian Blais (Bryant University), licensed under CC BY-SA 4.0 (dual-licensed under the GNU FDL 1.2 or later; this adaptation uses the CC BY-SA grant). Changes were made; this adaptation is distributed under the same license. License: CC-BY-SA-4.0.