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Tinkerplots: Interactive Data Analysis and Visualization Software

Tinkerplots helps you analyze data, create graphs, and generate reports to present your findings. Enter your own data or use sample datasets.

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Tinkerplots: Interactive Data Analysis and Visualization Software

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  1. Tinkerplots IV Carryn Bellomo Carryn.Bellomo@unlv.edu

  2. 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).

  3. 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

  4. Overview Cat Dataset

  5. 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.

  6. 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.

  7. 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?

  8. 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?

  9. 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?

  10. 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?

  11. 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?

  12. Entering Data Manually Finding Pi

  13. 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

  14. Entering Data Manually • Enter the following data:

  15. 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?

  16. 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?

  17. Data from the Web Population of Las Vegas

  18. Data from the Web • We can find data on housing at http://www.city-data.com/housing/houses-Las-Vegas-Nevada.html • 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.

  19. 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?

  20. 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:

  21. 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?

  22. Another Example Heaviest Backpacks

  23. 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

  24. 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?

  25. 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?

  26. Using DASL Education Levels

  27. Using DASL • The Data and Story Library is a great reference to use with your classes. • For the main menu, go to http://lib.stat.cmu.edu/DASL/ • 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.

  28. 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

  29. 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?

  30. 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.

  31. 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?

  32. 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%.

  33. Using DASL • Make another frequency distribution by category. • Do the answers to our questions change for this particular problem?

  34. Interesting Datasets Factors

  35. 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

  36. 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?

  37. 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?

  38. 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.

  39. Interesting Datasets Number Properties

  40. 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

  41. 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?

  42. Interesting Datasets – No. Properties • Select the “prime” attribute. • What are some possible patterns with prime numbers?

  43. 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!

  44. Conclusion • This presentation and handouts can be found at: http://www.unlv.edu/faculty/bellomo

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