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8.1
Types of Data
MDM - Term 3 Statistics
OBJECTIVES
Identify which pieces of data are quantitative and
which are categorical
Know several ways in which to organize data
Recognize which organizational representation would
be best for a particular set of data
Types of Data
When working with statistics, it’s important to recognize
different types of data.
Most data fall into one of two groups: quantitative
(numerical) and categorical.
Quantitative Data
These data pieces can be represented as a number or
have meaning as a measurement.
What information would be considered quantitative
data?
Quantitative Data
Examples
Height
IQ
Blood Pressure
A count of something (ie: Number of pets you own,
how many boys are in each classroom, etc.)
Quantitative Data
Quantitative data can be further broken into two
types: discrete and continuous.
Discrete data represent items that can be counted; they
take on possible values that can be listed out. (Shoe size,
clothing, etc.)
Continuous data represent measurements; their possible
values cannot be counted and can only be described using
intervals on the real number line. (How much gas in your gas
tank, height, etc.)
Identify Data
Identify the data as either discrete or continuous.
1. Grade percentage
2. Number of students in the class
3. How many colors are available
4. Distance travelled
5. How fast you run the 100 meter dash
Identify Data
Identify the data as either discrete or continuous.
1. Grade percentage continuous
2. Number of students in the class discrete
3. How many colors are available discrete
4. Distance travelled continuous
5. How fast you run the 100 meter dash continuous
Categorical Data
These data pieces are sorted or divided into
different categories, according to the attributes of
the data.
What information would be considered
categorical data?
Categorical Data
Examples
Colors
Type of music
Favorite animal
Gender
Subject matter
Identify Data
Identify the data as either quantitative or categorical.
1. Eye color categorical
2. Credits needed to graduate quantitative
3. Food categorical
4. Calories in food quantitative
5. Weight quantitative
Types of Data Representations
There are different ways to organize your data into
graphs, tables, or charts.
What are some ways you remember that could
organize data?
Types of Data Representations
Examples
Pie chart
Bar graph
Venn Diagram
Dot Plot
Line Graph
Scatter Plot
2-Way Table
Stem and Leaf Plot
Box and Whisker Plot
Types of Data Representations
You can use almost any type of data representation
you want but some are better than others for certain
types of data.
For example, you cannot use a scatter plot, stem and
leaf plot, or a box and whisker plot to represent
categorical data because they all require strictly
numerical data.
What’s Best?
Categorical
Pie Charts
Bar Graph
Venn Diagrams
2-Way Table
Quantitative
Scatter Plot
Stem and Leaf Plot
Box and Whisker Plot
Line Graph
Pie Charts & Bar Graphs (in intervals)
Pie Charts
Pie charts are a circular graphic divided into slices
based on the percentage.
That means that all the slices need to add up to 100%
Pie Charts
The chart to the left represents people’s
favorite colors.
Estimate the percentage of each color.
Pie Charts
A survey was taken on people’s favorite sport.
Basketball was 35%, football was 22%, baseball was
20%, 12% were other sports, and 11% don’t like sports.
Create a pie chart showing that data (make sure you
label!)
Bar Graphs
Bar Graphs are a graphical display of data using bars
of different heights.
Bar Graphs
A survey was taken on people’s favorite sport. 16
people liked basketball, 12 liked football, 10 liked
baseball, 10 liked other sports, and 4 don’t like sports.
Create a bar graph showing that data (make sure you
label!)
OBJECTIVES
Identify which pieces of data are quantitative and
which are categorical
Know several ways in which to organize data
Recognize which organizational representation would
be best for a particular set of data
Create a pie chart and bar graph
HOMEWORK
Assignment 8.1
EDPuzzle 8.1
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