Pre-test: Data Visualization

Download Data from GOOGLE DRIVE

What is the mtcars Dataset?

The mtcars dataset is a built-in dataset in R that contains specifications and performance metrics for 32 car models from the 1973–74 Motor Trend US magazine. It is commonly used for statistical modeling and visualization practice.

Variables in mtcars

Variable Description
mpg Miles/(US) gallon (fuel efficiency)
cyl Number of cylinders
disp Displacement (in cubic inches)
hp Gross horsepower
drat Rear axle ratio
wt Weight (1000 lbs)
qsec 1/4 mile time
vs Engine type (0 = V-shaped, 1 = straight)
am Transmission (0 = automatic, 1 = manual)
gear Number of forward gears
carb Number of carburetors

Use Cases (in business/engineering/automotive contexts)

  • Compare fuel efficiency across different engine types or transmission systems

  • Analyze relationship between weight and horsepower

  • Create predictive models for mileage

  • Visualize vehicle characteristics for marketing or design strategy

Use the mtcars sheet to create a plot.

Bar plot of cyl

You can use:

  1. Pivot Table: Insert → PivotTable → Drag Cylinders to Rows, and again to Values (set to “Count”).

  2. Then insert the chart from that summary.

Pie plot of cyl

You can use: 1. Pivot Table: Insert → PivotTable → Drag Cylinders to Rows, and again to Values (set to “Count”).

  1. Then insert the chart from that summary.

Jamovi intentionally does not include pie charts due to statistical and visual perception issues. This choice is based on best practices in data visualization from statistical and cognitive research.

Reasons Why Pie Charts Are Discouraged:

  1. Hard to compare angles: Humans are not good at judging angles or areas, especially when the slices are close in size. Bar charts are much easier to interpret.

  2. Poor for many categories: When a pie chart has more than 4–5 categories, it becomes cluttered and hard to read.

  3. No accurate axis: Pie charts don’t have a consistent baseline (unlike bar charts), which makes comparing values harder.

Note📚 Supported by Experts:

  • Edward Tufte, a pioneer in data visualization, famously called pie charts “the enemy of good design.”

  • Cleveland & McGill (1984): Their research showed bar charts were more accurate and easier for users to interpret than pie charts.

Histogram of mpg

  1. Select the mpg column.

  2. Go to the Insert tab.

  3. In the Charts group, click on Insert Statistic Chart.

  4. Choose Histogram.

Box plot

Group the data by number of cylinders (cyl) and place the corresponding mpg values into columns as shown.

mpg (4 cyl) mpg (6 cyl) mpg (8 cyl)
22.8 21.0 18.7
24.4 21.4 14.3
22.8 18.1 16.4
32.4 19.2 17.3
30.4 17.8 15.2
33.9 19.7 10.4
21.5 15.5 10.4
27.3 14.7
26.0 15.0
30.4 13.3
19.2
15.8
16.4
13.3

  1. Select all data including headers (mpg (4 cyl), mpg (6 cyl), mpg (8 cyl)).

  2. Go to the Insert tab.

  3. Click on Insert Statistic Chart → Select Box and Whisker.

Scatter plot of Hp vs MPG

1.Select the two columns: hp (Horsepower) and mpg.

  1. Go to the Insert tab.

  2. In the Charts group, click Insert Scatter (X, Y) Chart.

  3. Choose Scatter with only Markers (no lines).

Line plot

A line plot was created using the Gapminder sheet to visualize GDP per capita over time by country.

Use a PivotTable

Currently, Jamovi does not support time series data analysis.