1 / 43

Tinkerplots V

Tinkerplots V. 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).

wandabailey
Download Presentation

Tinkerplots V

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Tinkerplots V 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 • Just in Case – an Introduction • Determining the Value of a House • Changing Means and Medians • Connecting Line and Scatter Plots

  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. House Value

  13. House Value There are various websites that when given an address will provide you with comparables • www.zillow.com • Go to this site and see for yourself how it works • The data is summarized in HouseValues.tp • Download it: www.unlv.edu/faculty/bellomo “Grants” --> “7th Grade Connections” under “Prof Devt Seminars” [Keep this site open for future reference]

  14. House Value Open Tinkerplots • 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. • Drag a plot onto the page. • By default, data points are randomly arranged on the page.

  15. House Value Graph the square footage with sale price: • Click on the attribute for Sqft and drag it to the horizontal axis • Click on the attribute for SalePrice and drag it to the vertical axis • Drag any one data point to separate the data.

  16. House Value Questions: • Identify the house whose value we are trying to determine • Are there any homes with the same square footage? What did they sell for, and when?(use the reference line, if necessary) • Based on this, what would you estimate this house value to be?

  17. House Value Group the data based on square footage: • Click on a data point and drag it right to create about 5 categories • Click on the and buttons to see the mean and median. Based on this, what would you estimate this house value to be?

  18. House Value Determine the price per square footage: • Drag out the table • Create a new attribute by double clicking on “<new>” and typing “perSqft” • Right click on the title, and select “edit formula” • Type “SalePrice”, divided by (“/”) and “Sqft” • The values will be filled in automatically

  19. House Value Questions: • Identify the houses who sold for the most and least per square footage • Drag the “perSqft” attribute to the vertical, and stack • Determine the mean/median price per square foot • Click on the median/mean buttons, and display value Based on this, now what would you estimate this house value to be?

  20. House Value – Using Excel Use Excels Trendline to estimate the value: • Download the file HouseValues.xls from the website www.unlv.edu/faculty/bellomo • Create a chart and add a trendline (use the handout for instructions) Based on this, now what would you estimate this house value to be?

  21. Changing Means and Medians

  22. Changing Means and Medians Questions: • What is the difference between a mean and a median? • What effect does an outlier have on each?

  23. Changing Means and Medians • Download the file “Scooters.tp” from the website www.unlv.edu/faculty/bellomo • Drag the age attribute to the horizontal • Click on the mean and median buttons, and “show numeric value”

  24. Changing Means and Medians Questions: • What is the mean and median age for this data set? • Are there any outliers for this data set? • How much (as a percentage) do the mean and median change if the outlier is removed?[Click on the data point, go to the Plot menu and choose Hide Selected Cases].

  25. Changing Means and Medians • Add back the data value you removed[Go to the Plotmenu and choose Show Hidden Cases]. • Mix up the data • Make a new line plot of Age • Change the scale to go from the youngest to oldest [Double-click the box at the left end of the scale. Enter age for Axis starts at and click OK. Repeat on right].

  26. Changing Means and Medians Questions: • What is the lowest mean and median found by changing the oldest data point? • What is the highest mean and median found by changing the oldest data point? • What effect will adding a case have instead of changing the age of a given case?

  27. Changing Means and Medians • We can also analyze this in Excel. • Open the file “Scooters.xls” • You will see yellow boxes with means and medians. Click on the cells to see the formulas. • Again play around with the values to see the changes in the mean/median.

  28. Connecting Lines and Scatter Plots

  29. Connecting Lines and Scatter Plots Questions: • What is the relationship between a line plot and a scatter plot? • Where do data points appear on each of these plot types?

  30. Connecting Lines and Scatter Plots • Open the file “HallofFame.tp” • Make a line plot of “points_per_game”. • Take any one data point and determine how “points_per_game” is calculated from “points_total” and “game_total”.

  31. Connecting Lines and Scatter Plots • Use the dividers and percentages to determine the middle 50% of the data. • Click on the “Div” button • Click on “%” button to display percentages • Move the lines left and right to estimate a 25-50-25 split. What is the range of values of points per game for these players?

  32. Connecting Lines and Scatter Plots • Drag out a new plot, and graph “games_total” on the horizontal and “points_total” on the vertical. • Use the drawing tool to sketch a line so half the points fall below and half above. • Select points on the line plot at each interval to determine where they are on the scatter plot. • Use the mouse to click and drag a selected area containing those points • When you let go, these points will be highlighted

  33. Connecting Lines and Scatter Plots Question: • Where do data points appear on each of these plot types?

  34. Connecting Lines and Scatter Plots • We will repeat this exercise for free throws • Re-open the file “HallofFame.tp” • Make a line plot of “free_throw_percent”. • Take any one data point and determine how “free_throw_percent” is calculated from “free_throw_attempts” and “free_throws_made”.

  35. Connecting Lines and Scatter Plots • Use the dividers and percentages to determine the middle 50% of the data. • Click on the “Div” button • Click on “%” button to display percentages • Move the lines left and right to estimate a 25-50-25 split. What is the range of values of free throw percent for these players?

  36. Connecting Lines and Scatter Plots • Drag out a new plot, and graph “free_throw_attempts” on the horizontal and “free_throws_made” on the vertical. • Use the drawing tool to sketch a line so half the points fall below and half above. • Select points on the line plot at each interval to determine where they are on the scatter plot. • Use the mouse to click and drag a selected area containing those points • When you let go, these points will be highlighted

  37. Connecting Lines and Scatter Plots • Let’s use Excel to make our line and use it to predict values. • Open the table in Tinkerplots • Highlight the dataset by clicking “Edit” on the tools menu and “Select All” • Open Excel and click “Paste” • Format the data however you wish • If you have trouble copying, this file is on the web

  38. Connecting Lines and Scatter Plots • Follow the previous instructions to make a scatterplot of “free_throw_attempts” vs. “free_throws_made” • Add a trendline to determine the equation for the best fit line.

  39. Connecting Lines and Scatter Plots Questions: • What is the slope and intercept of the best fit line? • Use the slope and intercept to predict the free throws made for any one data point. • What does the slope indicate, in words? • The intercept?

  40. Connecting Lines and Scatter Plots Questions: • Is there a relationship between a players free_throw_percentage and field_goal_percentage? • How do you investigate this? • Are there any other attributes that relate to each other? Investigate.

  41. More Examples

  42. Connecting Lines and Scatter Plots Questions: • What would you estimate your home to be worth? • To take a look at some interesting datasets on the web, go to http://lib.stat.cmu.edu/DASL/

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

More Related