GEOG 250 Skill Check #1 Module 1 and Module 2

Qualitative Data

Categorical data that describe qualities, groups, or labels rather than numerical amounts.

Quantitative Data

Numerical data that represent measurements or counts where arithmetic usually makes sense.

Nominal Scale

A level of measurement made of categories with no meaningful order.

Ordinal Scale

A level of measurement made of categories that have a meaningful order or ranking.

Interval Scale

A numerical level of measurement with equal intervals but no true zero.

Ratio Scale

A numerical level of measurement with equal intervals and a true zero.

True Zero

A zero value that means none of the measured quantity is present.

Example of Nominal Data

Major, eye color, state, jersey number, or student ID.

Example of Ordinal Data

Class rank, poor/fair/good/excellent, or finishing place.

Example of Interval Data

Temperature in degrees Fahrenheit or Celsius.

Example of Ratio Data

Height, weight, age, rainfall, wind speed, or temperature in Kelvin.

Why is Fahrenheit interval data?

The differences between temperatures are meaningful, but 0°F does not mean no temperature exists.

Why is rainfall ratio data?

Zero inches means no rainfall occurred, and ratios are meaningful.

Why is a jersey number nominal?

It is only a label and arithmetic with the number does not have meaningful interpretation.

Population

The entire group that a study is interested in.

Sample

A smaller group taken from a population and actually observed or measured.

Variable

A characteristic or feature that can take different values.

Data

The individual values or observations collected in a study.

Statistic

A numerical value that describes a sample.

Parameter

A numerical value that describes a population.

Parameter Memory Trick

Parameter = Population; both start with P.

Categorical Variable

A variable that places observations into groups or categories.

Numerical Variable

A variable whose values represent measurable numerical quantities.

Bar Chart

A graph used mainly to compare amounts across categories.

Histogram

A graph used to show the distribution of one quantitative variable using numerical bins.

Scatterplot

A graph used to examine the relationship between two quantitative variables.

Line Graph

A graph commonly used to show how a quantitative variable changes over time.

Boxplot

A graph used to compare distributions and show median, quartiles, spread, and possible outliers.

Pie Chart

A graph used to show parts of a whole, although bar charts are often easier to compare.

Choropleth Map

A map where geographic areas are shaded or colored according to a data value.

When should you use a bar chart?

When comparing amounts or frequencies across categories.

When should you use a histogram?

When showing the distribution of a quantitative variable.

When should you use a scatterplot?

When studying the relationship between two quantitative variables.

When should you use a line graph?

When showing change or trends over time.

When should you use a boxplot?

When comparing the distributions of quantitative data between groups.

Bar Chart vs Histogram

A bar chart shows categories, while a histogram shows numerical ranges or bins.

Qualitative Color Scale

A color scheme using distinct colors to represent different categories without implying order.

Sequential Color Scale

A color scheme that progresses from light to dark or low to high values.

Diverging Color Scale

A color scheme that moves in two directions away from a meaningful midpoint.

Example of Qualitative Color Scale

Different colors for meteorology, geography, and geology majors.

Example of Sequential Color Scale

Light blue for low rainfall and dark blue for high rainfall.

Example of Diverging Color Scale

Blue for below normal, white for normal, and red for above normal.

Aesthetic Mapping

The process of connecting variables in a dataset to visual properties in a graph.

Common Aesthetics

x position, y position, color, size, shape, line type, and line width.

x aesthetic

Controls the horizontal position of observations.

y aesthetic

Controls the vertical position of observations.

color aesthetic

Uses color to represent a variable.

size aesthetic

Uses the size of a point or object to represent a variable.

shape aesthetic

Uses different shapes to represent categories.

What makes a good visualization?

It uses an appropriate chart type, clear title, labeled axes, units, readable text, logical colors, and minimal unnecessary clutter.

Chart Junk

Unnecessary visual elements that distract from the data.

Why are clear axis labels important?

They tell the viewer what variables and units are being displayed.

Why is a meaningful title important?

It helps the viewer immediately understand what the visualization is showing.

Why should colors be chosen carefully?

Color should help communicate categories, order, or values rather than confuse the viewer.

Distribution

The overall pattern of values in a quantitative dataset.

Frequency

The number of times a value or category occurs.

Frequency Table

A table showing how often different values or categories occur.

Low to High Data Color Choice

Sequential color scale.

Categories With No Order Color Choice

Qualitative color scale.

Values Above and Below a Midpoint Color Choice

Diverging color scale.

Major of a Student Measurement Scale

Nominal.

Poor, Fair, Good, Excellent Measurement Scale

Ordinal.

Temperature in Fahrenheit Measurement Scale

Interval.

Rainfall Amount Measurement Scale

Ratio.

Height Measurement Scale

Ratio.

Student ID Measurement Scale

Nominal.

Finishing Place in a Race Measurement Scale

Ordinal.

Temperature in Kelvin Measurement Scale

Ratio.

Favorite Weather Type Measurement Scale

Nominal.

EF Tornado Rating Measurement Scale

Ordinal.

Best Graph for Number of Students in Each Major

Bar chart.

Best Graph for Distribution of Student Heights

Histogram.

Best Graph for Temperature vs Electricity Usage

Scatterplot.

Best Graph for Temperature Over a 24-Hour Period

Line graph.

Best Graph for Comparing Exam Score Distributions Across Classes

Boxplot.

Best Color Scale for Annual Rainfall

Sequential.

Best Color Scale for Temperature Departure from Normal

Diverging.

Best Color Scale for Different Academic Majors

Qualitative.

How to identify nominal vs ordinal

Ask whether the categories have a meaningful order. If no, nominal. If yes, ordinal.

How to identify interval vs ratio

Ask whether zero means none of the quantity exists. If no, interval. If yes, ratio.

Basic Data Scale Decision Tree

Categorical with no order = nominal; categorical with order = ordinal; numerical without true zero = interval; numerical with true zero = ratio.

Basic Graph Decision Rule

Categories = bar; distribution = histogram; relationship = scatterplot; change over time = line graph.

What type of data does a histogram require?

Quantitative data.

What type of data does a scatterplot require?

Two quantitative variables.

What type of data does a bar chart usually display?

Categorical data with counts, frequencies, or numerical values for each category.

What is an outlier?

A value that is unusually far away from most other observations.

Median

The middle value of an ordered dataset.

Quartiles

Values that divide an ordered dataset into four sections.

Why can pie charts be harder to read?

People often have difficulty comparing angles and areas precisely.

What is the main purpose of data visualization?

To communicate patterns, relationships, comparisons, or trends in data clearly.

What is the main goal of DATA-1?

Determine which scale data belong to and explain why.

What is the main goal of DATA-2?

Choose an appropriate chart based on the data and create a visualization that is easy to understand.