1. Analyzing Categorical Data & Displaying Quantitative Data Section 1.1 & 1.2 Reference Text: The Practice of Statistics, Fourth Edition. Starnes, Yates, Moore

2. Starter Problem Antoinette plays a lot of golf. This summer she got a new driver and kept track of how far she hit her tee shots in several rounds. Look at these data (drive lengths in yards) and then write a few sentences that describe the lengths of her drives: 246260230233254203223193238220210237 270240192204250274220240235250222 230225241225230250200250226240

3. Today’s Objectives Analyze pie charts and bar graphs Two way tables: – Marginal Distribution –Conditional Distribution A Titanic Disaster Analyze Dot Plots Describe CUSS  your new best friend Stem and Leaf Plots: single, and back to back Histograms

4. Types of Variables Categorical variables record which group or category an individual belongs to. –What color is your hair? –What year are you in school? –What city do you live in? –Did the tee shot land in the fairway? –It does NOT make sense to average the results. Quantitative variables take on numeric values. –How tall is a person? –What score did a person get on the SAT? –How many desks are in a room? –How long was the tee shot? –It DOES make sense to average the results.

5. Visual Representation of Categorical Variables Categorical variables are typically represented by pie charts (for percents) or bar charts (percents or counts). Married?Count (M)Percent Single41.822.6 Married113.361.1 Widowed13.97.5 Divorced16.38.8

6. Dilbert comics Use a pie chart only when you want to emphasize each category’s relation to the whole. Pie charts are awkward to make by hand, but technology will do the job for you.

7. What Makes a Good Bar Graph? Good –All bars have the same width –X & Y axis’ labeled –Units –Title of Graph Bad –Bars have different widths –Pictures replacing the bars (see example next slide) –No labels

8. Why Is This A Bad Bar Graph? This ad for DIRECTV has multiple problems. How many can you point out?

9. Two Way Tables Two – way tables are a visual representation of the possible relationships between two set of categorical data. The categories are labeled at the top and the left side of the table, with the frequency info appearing in the interior cells of the table. The “totals” of each row appear at the right, and the “totals” of each column appear at the bottom.

10. “If you could have a new vehicle, would you want a sport utility vehicle or a sports car? Entries in the body of the table are called joint frequencies. The cells that contain the sum are called marginal frequencies.

12. Probability When looking at a relative frequency table the percent or ratio is also the probability of that event happening over the ENTIRE TOTAL. If a random selection was made, What's the probability a male selects an SUV? 21/240 If a random selection was made, What's the probability a female selects an SUV? 135/240 If a random selection was made, What's the probability that a SUV is selected? 156/240

13. Probability

14. Conditional probability When we are calculating the probability of an event occurring given that another event has occurred, we are describing conditional probability. Certain conditions have been preselected, and now we much calculate the probability based on that condition already happening. When we have conditional probability our denominator value becomes the column total or the row total depending on which condition is given. Example: What is the probability of selecting a sports car given a male? V.S. What's the probability a male selects an SUV?

15. Conditional Probability

16. Comparing Two Different Questions What's the probability a male selects an sports car? What is the probability of selecting a sports car given a male?

17. Flashback! Titanic Disaster On April 15, 1912, the Titanic struck an iceberg and rapidly sank with only 710 of her 2,204 passengers and crew surviving. Data on survival of passengers are summarized in the table below Survival Status Class of TravelSurvivedDiedTotal First Class201123 Second Class118166 Third Class181528 Total

18. Conditional Probability Survival Status Class of TravelSurvivedDiedTotal First Class201123324 Second Class118166284 Third Class181528709 Total5008171317

19. Break! - 5 Minutes

20. Section 1.2: Quantitative Data w/ Graphs Dotplots CUSS Histograms Stemplots

21. Types of Variables Categorical variables record which group or category an individual belongs to. –What color is your hair? –What year are you in school? –What city do you live in? –Did the tee shot land in the fairway? –It does NOT make sense to average the results. Quantitative variables take on numeric values. –How tall is a person? –What score did a person get on the SAT? –How many desks are in a room? –How long was the tee shot? –It DOES make sense to average the results.

22. Visual representation of Quantitative Variables: Dotplots The most basic method is a dotplot. –Every data point can be seen on the plot. Construction method: –Draw a horizontal axis with a scale that covers the full range of values for the variable. –Put a dot on (or above) the axis for each data point. –If data duplicate, stack them vertically. Construct a dotplot now of Antoinette’s drives: 246260230233254203223193238220210237 270240192204250274220240235250222 230225241225230250200250226240

23. Dotplot of Drive Data Based on the dotplot, estimate the center. –We see it around 230 or 240 yards. Estimate the spread. –Roughly from 190 to almost 280, so spread is about 90 yards. Describe the shape. –It appears “mound-shaped” with most of the data clustered at the center and with tails at each end.

24. C.U.S.S C: Center Median, where is it? –Mean can also describe the center, but is not resistant… U: Unusual data points Outliers! Are there any? We can calculate them…later in 1.3 S: Spread Describe the variability of the graph (largest value – smallest value) S: Shape How many peaks? Is the data clumped in a general location? Is data stretching to the right (skewed right). Is the data stretching to the left (skewed left). LASTLY…Always, ALWAYS C.U.S.S it out when describing graphs of data

25. Histograms Another important method is a histogram. –Individual data points cannot be seen on the plot. –Many data points are grouped together in vertical bars. Construction method: –Draw a horizontal axis with a scale that covers the full range of values for the variable. –Decide bar width (also called class width) so that 5 to 10 bars will cover the full range of data. –Set borders for bars, count frequencies, draw bars. –Use a vertical axis to show the bar height.

26. Histogram of Drive Data From a visual examination, estimate the center, unusual points, spread and the shape. (CUSS) –As before, you should see the center around 230 to 240, no unusual points, the spread looks like 90, and the shape still looks like a mound.

27. Stemplots AKA: Stem & Leaf Plots One way to organize numerical data is to make a stemplot. Lets turn to the board and walk through how to make a stemplot of the following data, found on pg 33 50 26 26 31 57 19 24 22 23 38 13 50 13 34 23 30 49 13 15 51

28. Stemplots check list Did we make a stemplot? Did we talk about splitting stems –1122334455…  upper and lower bounds Did we talk about back to back stemplots? Good…now we can move on

29. Percent of Population Over 65 by State 49 5 6 7 88 9 100029 11011344469 12003445556666 130133445677999 1423455 152379 16 17 186 Note: 4|9 = 4.9%

30. Today’s Objectives Analyze pie charts and bar graphs Two way tables: – Marginal Distribution –Conditional Distribution A Titanic Disaster Analyze Dot Plots Describe CUSS  your new best friend Stem and Leaf Plots: single, and back to back Histograms California Standard 14.0 Students organize and describe distributions of data by using a number of different methods, including frequency tables, histograms, standard line graphs and bar graphs, stem-and-leaf displays, scatterplots, and box-and-whisker plots.

31. Homework