Tinkerplots
Dr. Carryn Bellomo
UNLV Department of Mathematical Sciences
carryn.bellomo@ccmail.nevada.edu
Outline of Seminar
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Overview of Tinkerplots
Handouts
Classroom Activities
Conclusion
Overview of Tinkerplots
Helps you see trends and patterns in data
 Helps you make graphs and reports to
present findings
 There are sample data sets in:
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health
science and nature
social studies
sports
Overview of Tinkerplots
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The program has several movies, located
in the Help folder, such as:
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Adding Data (entering your own data set)
Comparing Groups (Occupational Data)
Exploring Relationships (Ozone Levels)
Making Common Graphs (Student Data)
Tinkerplot Basics (Cat Data)
Let’s view the Tinker Plots Basics Movie!
Handouts
The Tinkerplot Quick reference card will
help you troubleshoot and will serve as a
quick reference guide
 The activity handouts (beginning with the
Men’s 100m Dash) can be used as lesson
plans in the classroom. This is taken from
Exploring Data.pdf in the Help Folder.
 Excel “How To” handout
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Classroom Activities
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Old Faithful
Dinosaurs
Men’s 100-Meter Dash at the Olympics
Men and Women at the Olympics
Body Measurements
Australian Students
The Yo-Yo Mystery
Activity – Old Faithful
Here we will explore 222 eruptions of Old
Faithful, a geyser in Yellowstone National
Park, WY, in August 1978 and 1979
 The data cards given have information on
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Order number of observation
Year of observation
Day of month in August
Duration of eruption in minutes
Minutes to next eruption in minutes
Activity – Old Faithful
Let’s Think About This Before We Begin:
 A sign posted at the Old Faithful visitor's
center lets visitors know about how many
minutes it will be to the next eruption.
 To make these predictions, the park uses
a formula that “proves to be accurate, plus
or minus 10 minutes, 90% of the time.”
Activity – Old Faithful
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Open “Old Faithful.tp”
Located in:
Data and Demos  Science and Nature
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How should we organize the data to
predict the time to next eruption?
Activity – Old Faithful
Investigate the Data:
 There are two cases that do not have data
on “how long to the next eruption time”.
Case 106 and 222.
 Let’s see if we can use our analysis to
determine the time to the next eruption
Activity – Dinosaurs
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Here we will explore characteristics of dinosaurs
The data cards given have information on
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Name of dinosaur
Food preference
Sub-classification
Type of hip, and teeth
Average adult length, height, and weight
Number of limbs used for walking
Continent lived on
Geological period lived in, and no. of years ago
Activity – Dinosaurs
Let’s Think About This Before We Begin:
 Given the data we have, what kinds of
questions can we answer about
dinosaurs?
 Do we expect any relationships between
attributes?
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Weight vs. height
Hip type vs. diet…
Activity – Dinosaurs
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Open “Dinosaurs.tp”
Located in:
Data and Demos  Science and Nature
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How should we organize the data to
answer our questions?
Activity – Dinosaurs
Investigate the Data:
 Over the years of their existence, did
dinosaurs tend to get bigger, smaller, or
stay the same size?
 Did dinosaurs who ate meat (carnivores)
tend to be larger or smaller than those
who ate plants (herbivores)? If so, about
how different in size were these two
types?
Activity – Men’s 100m Dash
Here we will explore the winning times for
the men’s 100 meter dash from all the
Olympic games from 1896 to 2000
 The data cards given have much more
information than we actually need… all we
are looking for here is the year and the
men’s gold winning time for the 100m
dash
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Pages 32-34 of Activity Book
Activity – Men’s 100m Dash
Let’s Think About This Before We Begin:
 How many seconds do you think it would
take the fastest man today to run 100m
(about a football field)?
 Do you think this time is different today
than previous years? Why or why not?
Activity – Men’s 100m Dash
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Open “Olympics 100 Meter.tp”
Located in:
Data and Demos  Exploring Data Starters
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How should we configure our plot to
answer our questions?
Activity – Men’s 100m Dash
Investigate the Data:
 When was there the greatest change in
running times? Why do you think this is
so?
 What has happened to the running times
over the years? How could you account
for this?
 Can you project the times for future years?
Activity – Men’s 100m Dash
Side Note – Using Excel to Add Trendlines:
 You can add Linear and exponential
function trendlines in MS Excel
 This adds formality to the questions we
asked previously
Using Excel – Men’s 100m Dash
Copy the data and paste it into Excel
 Add a chart (scatterplot)
 Use excel to find the linear approximation
(least squares line)
 Use the equation to graph your own line,
and use it to predict missing or future
values
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“How To” specifics are on your excel handout
Activity – Men vs. Women
Here we will be comparing the winning
times/distances of men and women in the
Olympics over the years
 The data cards given have the gold medal
times for men and women for each year in
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100m
200m
High jump and
Long jump
Pages 35-36 of Activity Book
Activity – Men vs. Women
Let’s Think About This Before We Begin:
 Do you think there will be a difference in
the 100m dash between men and women?
If so, why, and by how much?
 If there is a difference between gold medal
times/distances, is it consistent throughout
the years? Or perhaps is the gap getting
smaller (or larger)?
Activity – Men vs. Women
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Open “Olympics Men Women.tp”
Located in:
Data and Demos  Exploring Data Starters
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How should we configure the data to get
the best answers to our questions?
Activity – Men vs. Women
Investigate the Data:
 With the 100m dash, does one gender out
perform another? If yes, by how much,
and is this consistent through the years?
 Let’s look at the 200m dash…
 Let’s look at an Excel file with this
information
Activity – Body Measurements
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Here we will explore characteristics of Body
measurements of adults (247 men and 260
women) who were exercising several hours a
week
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The data cards given have information on:
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Gender, age, weight, height
Pelvic diameter in centimeters
Chest depth and diameter in centimeters
Elbow, wrist, knee and ankle diameter in centimeters
Shoulder, chest, waist, abdominal, hip, thigh, bicep, forearm,
knee, calf, ankle and wrist girth in centimeters
Activity – Body Measurements
Let’s Think About This Before We Begin:
 Given the data we have, what kinds of
questions can we answer about these
measurements?
 Do we expect any relationships between
attributes?
Activity – Body Measurements
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Open “Body Measurements.tp”
Located in:
Data and Demos  Health
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How should we organize the data to
answer our questions?
Activity – Body Measurements
Investigate the Data:
 For which measurement are males and
females most different?
 For which measurement are they most
alike? Explain.
Activity – Australian Students
Here we will explore characteristics of 159
students in south Australia in grades 8-12
 The data cards given have information on:
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Gender, height in cm, birthday, grade level
Type of school, public/private
Travel time to school
Number of people in household
Type of driver's license, whether they have their own car
Whether they have their own mobile phone
Whether they have access to home computer, and Internet
Weekday hours spent watching TV before school
Activity – Australian Students
Let’s Think About This Before We Begin:
 Given the data we have, what kinds of
questions can we answer about these
students?
 Do we expect any relationships between
attributes?
Activity – Australian Students
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Open “Australian Students.tp”
Located in:
Data and Demos  Social Studies
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How should we organize the data to
answer our questions?
Activity – Australian Students
Investigate the Data:
 Is there evidence in these data of a gender
difference in pay? If so, about how big is
the difference?
 What differences do you notice, if any,
between public school students and
private school students?
Activity – The YoYo Mystery
Here we will be looking at computer driven
data from a yo-yo factory to determine
when a break in occurred
 The data cards given have
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Elapsed time
Hour
Period
Number_YoYos
Group
Pages 37-39 of Activity Book
Activity – The YoYo Mystery
Let’s Think About This Before We Begin:
 The manager is the prime suspect; he is
the last to leave and first to arrive. When
are his whereabouts unaccounted for?
Activity – The YoYo Mystery
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Open “Yo Yo Mystery.tp”
Located in:
Data and Demos  Exploring Data Starters
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How should we configure the data to
determine when the break-in occurred?
Activity – The YoYo Mystery
Investigate the Data:
 About what time could the break in have
taken place?
 With this information, could the suspect
have committed the break-in?
Conclusion
Conclusion
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This presentation and handouts can be
found at:
http://www.unlv.edu/faculty/bellomo