1. Stem-and-Leaf Plots …are a quick way to arrange a set of data and view its shape or distribution A key in the top corner shows how the numbers are split up They can look like this…

2. Key Points Order Numbers (suggested) Make a “T-Chart” Leaves are always the smallest place value Need a KEY!!

3. Try it, you’ll like it… 359, 357, 348, 347, 337, 347, 340, 335, 338, 348, 339, 356, 336, 358

4. Example 2 8.9, 8.8, 7.2, 7.5, 9.2, 7.9, 8.2, 9.1, 8.7, 8.2, 8.5, 8.6, 9.5, 7.5

5. Try two on your own!!!!

6. Histograms (Bar Graphs) They show the frequency of data

7. Key points!! Sideways stem-and-leaf plot. Divide range into classes! Count number of observations in each class. (make a frequency table) One observation cannot fall into 2 classes. Label axes and title your graph No space between bars!!!! (unless freq=0) Common to add a break in the scale (if axes don’t need to start at 0)

8. Lets try one!! 5, 4, 6, 7, 9, 2, 3, 9, 6, 9, 3, 2, 8, 10, 10

9. Try two on your own!! Hint group #2 by 2’s.

10. End of today!

11. 12.3 – Box and Whisker Plot LEQ: How do we create and interpret Box and Whisker Plots? Vocab: ◦Quartiles ◦Range ◦Interquartile Range ◦Outlier ◦5-Number Summary

12. What are they for… A Box and Whisker plot basically spreads out the data into 4 sections. Each quarter holds 25% of the data.

13. How is it split up There are 5 points that break the data… ◦Minimum Value ◦1 st Quartile – Q1 ◦Median – Q2 ◦3 rd Quartile – Q3 ◦Maximum Value

14. So what do I do? Put the data in order. Find the median. Without using the median, find the upper (Q3) and lower (Q1) medians. Draw and label a number line that includes all of your data. Plot your points above the line and connect the dots.

15. More notes… The Range = Maximum – Minimum The Interquartile Range (IQR) = Q3 – Q1 If 2 numbers are in the middle, meet halfway like you did before

16. Try This… 2528313634 3830283533 2630292734

17. Work = p786 # 7,9,11

18. 1.5 – Scatter Plots and Least-Square Lines LEQ: How do we draw conclusions about correlation between variables?  Vocab: Scatter Plot Correlation Correlation Coefficient Least-Square Lines

19. Scatter Plots… show a relationship between 2 variables. Some real-world examples could be Age vs Height or Time vs Distance

20. Least-Square Line… also called a Line of Best Fit. Imagine a line going right through all of the points, like an average.

21. Correlation… is a description about how the data points cluster together.

22. Correlation Coefficient… …is denoted by ‘r’ and indicates how closely the data points cluster. It is a value that can vary from -1 to 1. A perfect negative correlation is r = - 1. A perfect positive correlation is r = 1. The tighter the cluster of points, the closer the correlation is to +1 or -1.

23. For example…

24. Work Page 41 #13, 14- Graph the points and draw a Line of Best Fit. Is the correlation weak or strong, positive or negative. #15-20 – Match the r values with the correct graph.