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Tinkerplots IV. Carryn Bellomo Carryn.Bellomo@unlv.edu. What Tinkerplots Does. Helps you see trends and patterns in data. Helps you make graphs and reports to present findings. There are sample data sets, or you can enter your own data (collected in class or on the internet).

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Tinkerplots iv

Tinkerplots IV

Carryn Bellomo


What tinkerplots does
What Tinkerplots Does

  • Helps you see trends and patterns in data.

  • Helps you make graphs and reports to present findings.

  • There are sample data sets, or you can enter your own data (collected in class or on the internet).

Presentation overview
Presentation Overview

  • Overview of Tinkerplots (cat data)

  • Entering Data Manually (finding Pi)

  • Data from the Web (housing prices)

  • Another Example (heaviest backpacks)

  • Using DASL (education levels)

  • Interesting Datasets

    • Factors

    • Number properties



Cat Dataset

Overview cat dataset
Overview – Cat Dataset

Open Tinkerplots with “Cats,” located under “Science and Nature”

  • At the top left you have data cards, 1 card for each data point.

  • Attributesare assigned to each data point, they can be continuous or discrete.

  • By default, data points are randomly arranged on the page.

Overview button explanations
Overview – Button Explanations

  • Stack arranges them in a line.

  • Order arranges them numerically or by category.

  • Label puts their name next to the icon.

  • The “Mix up button” randomly places the icons on the screen.

Overview arranging data
Overview – Arranging Data

  • We want to arrange the cats by weight.

  • Let’s order the cats by weight, and put their names by their icon:

    • Click on the weight attribute

    • Click on the order button, then click on the stack button

    • Then click on the name attribute, and then the label key

  • Who is the heaviest, the lightest?

Overview grouping data
Overview – Grouping Data

  • Let’s make a bar graph of the cats with their body length:

    • Select the body length attribute

    • Pull an icon right to separate the data, and continue to pull on them until they are fully separated

    • Then stack them, and change the icon if you like to “fused rectangular”

  • What do you notice about the data?

Overview further analyzing
Overview – Further Analyzing

  • There seem to be two clusters of cats regarding body length. Perhaps this is related to age or gender?

    • Click on the attribute for age. Does there seem to be a relationship?

    • Click on the attribute for gender. Does there seem to be a relationship?

  • How can you tell?

Overview further analyzing1
Overview – Further Analyzing

  • Separate the males and females by selecting the gender attribute and dragging one of the icons up.

  • Click on the button to see the mean, and the button for a reference line.

  • What can you conclude?

Overview further analyzing2
Overview – Further Analyzing

  • Perhaps body length is related to weight?

    • Click on the body length attribute, and pull right to fully separate the data

    • Click on the weight attribute, and pull up to fully separate the data

  • What do you think about the relationship between body weight and length?

Entering data manually1
Entering Data Manually

  • Students can collect data, which you can enter manually.

    • Open Tinkerplots

    • Choose “new” from the file menu

    • Click and drag a table into the screen

    • Enter column titles:ObjectCircumference, and Diameter

Entering data manually2
Entering Data Manually

  • Enter the following data:

Entering data manually3
Entering Data Manually

  • Let’s determine if there is a relationship between circumference and diameter

    • Click on the attribute for diameter and drag it to the horizontal axis.

    • Click on the attribute for circumference and drag it to the vertical axis.

    • Fully separate the data

  • Is there a relationship? How can you tell?

Entering data manually4
Entering Data Manually

  • We suspect that Circumference/Diameter would be a constant value.

  • Let’s add another column with this calculation.

    • In the table, add a new column heading.

    • Right click on this heading, and click “Edit Formula”

    • Under attributes, find “Circumference” double click on it.

    • Click on the division symbol

    • Double click on “Diameter”

    • Click “OK”

  • What have we learned about this relationship?

Data from the web

Data from the Web

Population of Las Vegas

Data from the web1
Data from the Web

  • We can find data on housing at


  • Go to the site above, and find “Estimate of home value of owner-occupied houses in 2000.”

  • We will reproduce the graph you see below the data table.

Data from the web2
Data from the Web

  • Get the data into Tinkerplots

    • Open a new file

    • Drag out a set of datacards

    • Click on “Edit” in the menu, then “Paste Cases”

  • What happened?

Data from the web3
Data from the Web

  • We need to format the data so it enters correctly.

  • This can be done in a variety of formats, the easiest is probably notepad.

  • The format below will allow you to paste:

Data from the web4
Data from the Web

  • Drag “Price” to the horizontal axis.

  • Click on the attribute for “total” and then change the icon to “value bar vertical”.

  • If the items are not ordered correctly. You can change the order by clicking on the label and dragging left or right.

  • What kinds of questions can you answer with this dataset?

Another example

Another Example

Heaviest Backpacks

Heaviest backpacks
Heaviest Backpacks

  • Here we will explore the backpack weights of students

  • The data cards given have information on

    • First name of student

    • Gender of student

    • Grade level of student

    • Weight of student in pounds

    • Weight of student’s backpack in pounds

Heaviest backpacks1
Heaviest Backpacks

  • Open “Heaviest Backpacks.tp”Located in:Data and DemosExploring Data Starters

  • What kind of relationships do we expect to find?

  • How should we organize the data?

Heaviest backpacks2
Heaviest Backpacks

Investigate the Data:

  • Is there a relationship between packweight and grade? Compare the means.

  • Do girls tend to carry lighter backpacks than boys?

  • Does a person who weighs more carry a heavier pack?

Using dasl

Using DASL

Education Levels

Using dasl1
Using DASL

  • The Data and Story Library is a great reference to use with your classes.

  • For the main menu, go to


  • To find the dataset for Education, follow:“List all topics”  “Education”  “#4 Educational Attainment”

  • This is the story behind the data. Click on “Education by Age” to see the dataset.

Using dasl2
Using DASL

Get the data into Tinkerplots:

  • Highlight the data on the webpage (including column titles)

  • Copy the data by holding down the Control key and pressing C

  • Go to a blank page in Tinkerplots

  • Pull out a stack of data cards

  • Go to Edit, then Paste Cases

Using dasl3
Using DASL

Investigate the Data to Answer:

  • For 1984, what age group has the most people with 4+ years of college?

  • What age group has the most high school dropouts?

  • To what social events can you attribute to these patterns?

Using dasl4
Using DASL

We would like a frequency distribution:

  • Arrange the data by age group along the horizontal (put the categories in order).

  • Click on the attribute for count, and change the icon to “value bar vertical”.

  • Then click on the “Education” attribute.

  • Click on “key” so you can clearly see categories.

Using dasl5
Using DASL

  • Just because a group has the “most” doesn’t take into account the size of the population.

  • How can this skew our analysis and what should we do to correct for it?

Using dasl6
Using DASL

Calculate the percentage for each category

  • Calculate the total number of people in each age group.

  • Divide each “Count” by the “Totals” found above.

  • Multiply by 100%.

Using dasl7
Using DASL

  • Make another frequency distribution by category.

  • Do the answers to our questions change for this particular problem?

Interesting datasets factors
Interesting Datasets – Factors

  • This dataset/activity explores patterns related to multiplication.

  • The datacards contain properties of the numbers 1 to 100.

  • Open “Factors.tp”Located in:Data and DemosExploring Data Starters

Interesting datasets factors1
Interesting Datasets – Factors

  • When we resize the plot to make it 3 units wide and click on the “factor 3” attribute, what do we notice?

  • What is the generalization to this?

Interesting datasets factors2
Interesting Datasets – Factors

  • When we think of the division problem , we know 3 groups of 8 make 24.

  • This can be simulated by making a stack 8 units wide. Clicking on the “factor 8” attribute, find 24. We see it is evenly divisible and the result is the 3rd row!

  • Or, make the stack 24 wide (keep “factor 8” attribute selected). What do you notice?

Interesting datasets factors3
Interesting Datasets – Factors

  • Experiment with this dataset on your own.

  • What other patterns do you notice that could help your students?

  • The file “Exploring Data.pdf” located in the “Tinkerplots Help” directory has a guided activity for you to use in your classroom.

Interesting datasets1

Interesting Datasets

Number Properties

Interesting datasets no properties
Interesting Datasets – No. Properties

  • This dataset/activity explores number properties such as perfect squares, and prime numbers.

  • The datacards contain properties of the numbers 1 to 100.

  • Open “Number Properties.tp”Located in:Data and DemosExploring Data Starters

Interesting datasets no properties1
Interesting Datasets – No. Properties

  • What kind of patterns do you notice with your plot 4 wide and the “perfect_square” attribute selected?

  • What other plot sizes give you good patterns for squares?

Interesting datasets no properties2
Interesting Datasets – No. Properties

  • Select the “prime” attribute.

  • What are some possible patterns with prime numbers?

Try it yourself
Try It Yourself !

  • Investigate a topic that interests you

    • This could be data from the internet, or

    • Design a lesson with data you can collect with your students

  • Share with us your ideas!


  • This presentation and handouts can be found at: