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Glossary

A

Axes labels (graph component)

Criticality: 3

Text descriptions on the horizontal (x-axis) and vertical (y-axis) of a graph that indicate what each axis represents and its units.

Example:

Misinterpreting the axes labels, such as confusing 'years' with 'months', can lead to incorrect conclusions from a graph.

B

Bar graphs

Criticality: 2

Graphs that use rectangular bars of varying heights or lengths to compare discrete categories or groups of data.

Example:

A bar graph could effectively compare the number of students who prefer different subjects like Math, Science, or English.

Box plots

Criticality: 2

Graphical displays that summarize the distribution of a dataset using five key values: minimum, first quartile (Q1), median, third quartile (Q3), and maximum.

Example:

A box plot can quickly show the spread and central tendency of a class's test scores, highlighting any potential outliers.

C

Correlation vs. Causation

Criticality: 3

Correlation indicates that two variables move together, while causation means one variable directly causes a change in the other; correlation does not imply causation.

Example:

Observing that ice cream sales and drowning incidents both increase in summer shows correlation, but ice cream doesn't cause drowning; the underlying cause is hot weather.

D

Data points (graph component)

Criticality: 1

Individual pieces of information plotted on a graph, representing specific measurements or observations.

Example:

Each data point on a scatterplot might represent a student's height and weight.

F

Footnotes (graph component)

Criticality: 1

Additional notes or explanations placed at the bottom of a graph, providing context, sources, or important details about the data.

Example:

A footnote might clarify that the data presented in the graph only includes participants from a specific age group.

H

Histograms

Criticality: 2

Graphs that display the frequency distribution of a continuous dataset, using bars to represent data within specific numerical ranges or bins.

Example:

A teacher might use a histogram to show the distribution of scores on a recent exam, grouping scores into ranges like 70-79, 80-89, etc.

I

Interquartile range (IQR)

Criticality: 2

A measure of statistical dispersion, calculated as the difference between the third quartile (Q3) and the first quartile (Q1), representing the middle 50% of the data.

Example:

The interquartile range is useful for understanding the spread of the central part of the data, less affected by extreme values.

L

Legend (graph component)

Criticality: 1

A key or guide on a graph that explains the meaning of different colors, symbols, or line styles used to represent various data series.

Example:

If a graph shows multiple lines, the legend will tell you which line represents 'Group A' and which represents 'Group B'.

Line graphs

Criticality: 2

Graphs that display data points connected by lines, primarily used to show trends or changes in data over a continuous period, such as time.

Example:

To visualize how a student's test scores improved throughout the semester, a line graph would clearly show the upward trend.

M

Mean

Criticality: 3

The average of a dataset, calculated by summing all values and dividing by the total number of values.

Example:

To find the mean score of a class, you add up all the students' scores and divide by the number of students.

Median

Criticality: 3

The middle value in a dataset when the values are arranged in numerical order.

Example:

In the dataset {2, 5, 8, 10, 12}, the median is 8, as it's the central value.

Mode

Criticality: 1

The value that appears most frequently in a dataset.

Example:

In a list of favorite colors, if 'blue' is chosen by the most people, then 'blue' is the mode.

N

Negative correlation

Criticality: 3

A relationship between two variables where one tends to increase as the other decreases.

Example:

You might observe a negative correlation between the number of hours spent watching TV and academic performance.

No correlation

Criticality: 2

A situation where there is no discernible relationship or pattern between two variables.

Example:

There is typically no correlation between a person's favorite color and their height.

O

Outliers

Criticality: 3

Data points that are significantly different from other observations in a dataset, potentially skewing statistical measures.

Example:

If most students score between 70-90 on a test, but one student scores 20, that 20 is an outlier.

P

Patterns

Criticality: 2

Recurring regularities or arrangements within a dataset, which can include clusters, gaps, or cyclical behaviors.

Example:

A scientist might look for patterns in weather data, such as a recurring cold front every winter.

Positive correlation

Criticality: 3

A relationship between two variables where both tend to increase or decrease together.

Example:

There is often a positive correlation between the amount of time spent exercising and an individual's fitness level.

R

Range

Criticality: 2

A measure of spread calculated as the difference between the maximum and minimum values in a dataset.

Example:

For test scores from 60 to 95, the range is 35 (95 - 60).

S

Scales (graph component)

Criticality: 2

The numerical ranges and intervals marked along the axes of a graph, indicating how the data values are measured and spaced.

Example:

Paying attention to the scales on a graph is crucial; a compressed scale can make small changes appear significant.

Scatterplots

Criticality: 3

Graphs that show the relationship between two different numerical variables for a set of data, with each point representing a pair of values.

Example:

A scatterplot could illustrate the relationship between the number of hours a student studies and their corresponding test score.

Standard deviation

Criticality: 3

A measure of the average amount of variability or dispersion of data points around the mean of a dataset.

Example:

A small standard deviation indicates that data points are clustered closely around the mean, while a large one means they are more spread out.

T

Tables and graphs

Criticality: 3

Visual tools used to organize and display data, making complex information easier to understand and interpret.

Example:

A scientist might use a table and graph to present the results of an experiment on plant growth over several weeks.

Title (graph component)

Criticality: 2

The main heading of a graph that clearly states what the graph represents or the data it displays.

Example:

Always check the title of a graph first to understand its main purpose, like 'Average Daily Temperatures in July'.

Trends

Criticality: 3

General directions or patterns observed in data over time or across categories, such as increasing, decreasing, or constant movement.

Example:

Analyzing the stock market, you might observe an upward trend in a company's share price over the last quarter.