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Data Collection And Displays

16 concepts in Statistics

Data collection and displays are where statistical thinking becomes visible. Students begin by asking statistical questions, deciding how data should be collected, and choosing displays that match the type of data they have. They learn that a graph is not just decoration: it is a claim about what matters in the data and what patterns the viewer should notice first. This topic covers categorical and numerical data, frequency tables, bar graphs, line plots, histograms, box plots, pie charts, and stem-and-leaf plots, along with the common display mistakes that make data look more dramatic or more certain than it really is. A strong foundation here matters because every later statistics topic depends on representing data honestly before summarizing or interpreting it.

Suggested learning path: Start with statistical questions, data collection, and categorical versus numerical data, then move through tables and simple graphs before reading richer displays such as histograms, box plots, pie charts, and stem-and-leaf plots.

Data Collection

The systematic process of gathering information to answer questions, using methods like surveys, experiments, or observations.

Prerequisites:
tally chart

Statistical Question

A statistical question is a question that anticipates variability in answers โ€” it cannot be answered with a single fixed number because different data points will give different responses. It requires collecting data from multiple sources to answer.

Prerequisites:
data collection

Categorical Data

Categorical data is data that can be sorted into groups or categories, like colors, types, or names, rather than measured with numbers. You can count how many items fall into each category, but you cannot meaningfully add, subtract, or average the category labels themselves.

Prerequisites:
tally chart

Data Representation

Data representation is the process of organizing and displaying data using charts, graphs, or tables so that patterns, trends, and comparisons become easier to see and understand at a glance.

Prerequisites:
data collection
tally chart

Tally Chart

A tally chart is a simple way to record and count data using vertical strokes called tally marks. Every fifth mark is drawn diagonally across the previous four, making groups of five that are easy to count. For example, |||| represents 4 and โงธ|||| represents 5.

Frequency Table

A frequency table is a table that records how often each value or category occurs in a data set, organizing raw data into a clear summary with categories in one column and their counts (frequencies) in another.

Prerequisites:
tally chart

Pictograph

A pictograph (or picture graph) displays data using pictures or symbols, where each picture represents a specific quantity. For example, if ๐ŸŽ = 5 apples, then ๐ŸŽ๐ŸŽ๐ŸŽ means 15 apples. A key (legend) always tells you what each symbol represents.

Prerequisites:
tally chart

Bar Graph

A bar graph is a chart that uses rectangular bars of different heights or lengths to compare quantities across distinct categories. Each bar represents one category, and the bar's length is proportional to the value it represents.

Prerequisites:
stat data representation
tally chart

Line Graph

A line graph is a chart that uses points connected by straight line segments to show how a quantity changes over time or across a continuous variable. The horizontal axis typically represents time, and the vertical axis represents the measured value.

Prerequisites:
stat data representation

Line Plot (Dot Plot)

A line plot (also called a dot plot) is a diagram that displays data values as marks โ€” usually X's or dots โ€” stacked above their corresponding values on a number line. Each mark represents one data point, making it easy to see the frequency of each value.

Prerequisites:
tally chart

Dot Plot

A dot plot is a statistical chart that displays the frequency of data values using dots stacked above a number line. Each dot represents one observation, making it easy to see clusters, gaps, and the overall shape of a distribution for small to medium datasets.

Prerequisites:
line plot
frequency table

Pie Chart

A pie chart is a circular graph that shows how a whole is split into categories. Each sector represents a category, and the size of the sector is proportional to that category's share of the total.

Prerequisites:
stat data representation
categorical data

Stem-and-Leaf Plot

A stem-and-leaf plot displays numerical data by splitting each value into a stem and a leaf. It shows the distribution of the data while keeping the original values visible.

Prerequisites:
frequency table
dot plot

Histogram

A histogram is a graph that groups numerical data into equal-width ranges (bins) and shows the frequency of values in each range using adjacent bars that touch. Unlike bar graphs, histograms display the distribution shape of continuous data.

Prerequisites:
bar graph
stat range

Box Plot

A visual display of the five-number summary: minimum, first quartile (Q1), median, third quartile (Q3), and maximum.

Prerequisites:
median intro
stat quartiles

Misleading Graphs

Misleading graphs are data visualizations that distort the truth through techniques like truncated axes, inconsistent scales, cherry-picked time ranges, or manipulated aspect ratios to create false impressions and lead viewers to wrong conclusions.

Prerequisites:
bar graph
line graph
stat data representation

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