Transcript Relationships Between Quantitative Variables

Chapter 2
– Class 11
Turning Data
Into Information
Use table and/or graph
to represent
Categorical Data
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Homework Check
• Assignment:
• Chapter 2 – Exercise 2.8 and 2.11
Suggested Answer – 2.8
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Suggested Answer – 2.11
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2.3 Summarizing One or Two
Categorical Variables
Numerical Summaries
• Count how many fall into each category.
• Calculate the percent in each category.
• If two variables, have the categories of
the explanatory variable define the rows
and compute row percentages.
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Example 2.1
Seatbelt Use by Twelfth-Graders
2003 nationwide survey of American HS students
“How often do you wear a seatbelt when driving a car?”
• Total sample size n = 3042 students.
• A majority, 1686/3042 =
.554, or 55.4%, said they
always wear a seatbelt,
while 115/3042 = .038,
or 3.8%, said they never
wear a seatbelt.
• Rarely or never:
8.2% + 3.8% =12%
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Example 2.1
Seatbelt Use by Twelfth-Graders
Are females more likely to say always wear seatbelt?
Are males more likely to say rarely or never wear seatbelt?
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Females: 915/1467 = 62.4% said always wear seatbelt
Males: 771/1575 = 49.0% said always wear seatbelt.
Males: 10.5% + 5.7% =16.2% rarely or never wear one.
Females: 5.7% + 1.7% = 7.4% rarely or never wear one.
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Distribution of a Variable
• What are the variables here?
• What kind of variables are they?
• What does it mean by distribution of a variable?
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Roundoff Errors
• Find the total number of persons and total percent
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Key Terminologies
• Distribution of a variable
– describes how often the possible responses occur
• Roundoff errors
– Errors in arithmetic when the numbers of a total are
rounded separately
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Pie Charts
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Bar Graph / Bar Chart
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Quick Check
Use a pie chart and bar graph to display the
following data given
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Homework
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Assignment:
Chapter 2 – Exercise 2.27 and 2.32
Reading:
Chapter 2 – p. 20-23