1. Friday Lesson Do Over
Statistics is all about data. There is a story to be uncovered behind the data--a story with characters, plots and problems. The questions or problems addressed by the data and their story can be disappointing, exciting, or meh.

3. Displays of Data--Warm Up
Dot Plot: A plot of each data value on a number line.
Yakov says the average delay is 1 hour. Do you agree or disagree? Why?
Is the mean or median a better description of a typical time delay?Why?

4. Categorical vs Quantitative Data
Categorical Data: color, sex, race, rank, frequency, size, subject, pedigree, income status
Quantitative: age, height, weight, distance, percentages, volume, miles,

5. Histogram

6. „ Steps in Making a Histogram
1. Choose the classes by dividing the range of data into classes of equal width (individuals fit into one class).
2. Count the individuals in each class (this is the height of the bar).
3. Draw the histogram: ƒ The horizontal axis is marked off into equal class widths. ƒ The vertical axis contains the scale of counts (frequency of occurrences) for each class.

7. Describing Data:
C.U.S.S.
Center:
Mean:
Median:
Mode:

8. Box and Whisker

10. Unusual Data (creating a box and whisker plot)
Outlier Rule:
1. Arrange data in order. 2. Calculate first quartile (Q1), third quartile (Q3) and the interquartile range (IQR=Q3-Q1). CO2 emissions example: Q1=0.9, Q3=6.05, IQR= Compute Q1–1.5 × IQR (=– 6.825) Compute Q3+1.5 × IQR (=13.775) Anything outside this range is an outlier.

11. Spread

12. Shape--skew