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Tinkerplots IV

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Tinkerplots IV

Carryn Bellomo

Carryn.Bellomo@unlv.edu

- 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).

- 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

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.

- 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.

- 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?

- 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?

- 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?

- 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?

- 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 Manually

Finding Pi

- 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

- Enter the following data:

- 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?

- 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

Population of Las Vegas

- 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.

- 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?

- 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:

- 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

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

- Open “Heaviest Backpacks.tp”Located in:Data and DemosExploring Data Starters
- What kind of relationships do we expect to find?
- How should we organize the data?

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

Education Levels

- 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.

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

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?

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.

- 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?

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%.

- Make another frequency distribution by category.
- Do the answers to our questions change for this particular problem?

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 DemosExploring Data Starters

- 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?

- 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?

- 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 Datasets

Number 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 DemosExploring Data Starters

- 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?

- Select the “prime” attribute.
- What are some possible patterns with prime numbers?

- 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:
http://www.unlv.edu/faculty/bellomo