1. What is Statistics?
Day 2.

2. Statistics Collecting data Organizing data Analyzing data
Drawing conclusions

3. Population
All individuals/objects we want to study

4. Sample
Subset of population
Reasonable size to study

5. Population/Sample
After a major earthquake in California, insurance agents want to estimate the monetary value of damage to single-family homes in San Francisco.
One hundred single-family homes in San Francisco were randomly selected for inspection.
Describe the population and sample for this study.
Population: All single-family homes in San Francisco
Sample: 100 homes selected for inspection

6. Variable
Characteristic we're studying

7. Data
Observations of variable(s)

8. Let's Make Some Graphs!

9. Favorite Music Genre Univariate Data: One variable Genre Alternative
Classical
Country
Frequency 16 4 15
Genre
Pop
Rap
Rock
Other
Frequency 35 21 18 16
Univariate Data: One variable

10. U of M vs. MSU by Gender Bivariate Data: Two variables
Male
Female
U of M 20 16
MSU 10
Neither 3 1
Bivariate Data: Two variables
(Multivariate Data: More than 2 variables)

11. Bar Graph Bars do not touch
Describe: Which category occurred most or least often?
For bivariate data: double or segmented bar graph

12. Pie Chart Slice angle = proportion (%) 360°
Describe: Which category occurred most or least often?
End of day 1

13. Fastest Speed Driven
End of day 1

14. Categorical Variables
Data is in categories
Also called qualitative
Ex.: Gender, Type of Car
Use a bar graph or pie chart

15. Numerical Variables Data is in numbers Also called quantitative
Ex: Speed, shoe size
Must make sense to find the average
Phone number: Not numerical!

16. Dotplot Dots (or X's, *'s, etc.) on a number line
Comparative dotplot: One number line, multiple plots
Sometimes you see other markings, like X's – still a dotplot!

17. Describing a univariate numerical graph
Have students do Features of Distributions in groups first, then go through this

18. What strikes you as the most distinctive difference among the distributions of exam scores in classes A, B, & C ?

19. Center
Where is the middle of the data (roughly)?

20. What strikes you as the most distinctive feature(s) of the distribution of exam scores in class K?

21. Unusual things Gaps, clusters, anything else unusual
Outliers: values that lie far away from the rest of the data
Gaps, clusters, anything else unusual
 CUSS!

22. What strikes you as the most distinctive difference among the distributions of scores in classes D, E, & F?
Class

23. Spread How spread out is the data? How much variability is there?
Range = maximum – minimum

24. What strikes you as the most distinctive difference among the distributions of exam scores in classes G, H, & I ?

25. Shape
What overall shape is the distribution?
Distributions Activity

26. Shapes of Distributions
Day 3 – Intro with results of distributions activity

27. Symmetrical Sides are (more or less) mirror images
Special type: bell curves

28. Uniform
Every value has (more or less) equal frequency

29. Skewed (left or right) One side (tail) is longer than the other
Skewness is fewness!
Skewed left (negatively skewed)
Skewed right (positively skewed)
Show example of skewed left and skewed right

30. Bimodal (or multi-modal)
Two (or more) separate peaks
Go back to distributions activity & sort into the four types

31. ***CONTEXT*** Descriptions must: Include the context
Use statistical vocabulary
"Bell curve"

32. Fastest Speed Driven
End of day 1

33. Height (inches) Females: 70 66 65 68 68 68 67 64 61 66 66 64 71 70
Males:
End of day 1

34. More numerical graphs

35. Stemplot (stem & leaf plot)
Stem = 1st digit, Leaves = rest of digits
Leaves in increasing order
Commas only with double-digit leaves
Include a key
Can split stems with long leaves
Back to back stemplot: two sets of data
Show example of split stems.

36. Price per ounce for various brands of shampoo at a grocery store:
Do on board

37. PLAN test scores for a sample of sophomores:
Do on board

38. Total tobacco exposure time (in seconds) for Disney G-rated movies:
Total tobacco exposure time (in seconds) for other studios’ G-rated movies:
Do on board

39. Histogram Bar graph for numerical data Bars touch
Data is grouped into classes (intervals)
y-axis options:
frequency (how many data points in each class)
relative frequency (percent of data in each class)
Two types:
Discrete: Bars are centered over discrete values
Continuous: Bars cover a class (interval) of values
Draw a picture of each type with survey data

40. Discrete (numerical) data
Listable set of numbers
We're counting

41. Continuous (numerical) data
Any value in the variable's domain is possible
We're measuring

42. Identify the type of variable:
Income of adults in your city
Color of M&M candies selected at random from a bag
Number of speeding tickets each student in AP Statistics has received
Area code of an individual
Birth weight of female babies born at a large hospital over the course of a year
Numerical
(Continuous)
Categorical
Numerical
(Discrete)
Categorical
Numerical
(Continuous)

43. Number of Pieces of Gum Chewed Per Day:
Do on board

44. 2011 Life Expectancies at Birth in Each of the 54 Countries in Africa:
Do on board

45. Frequency Table for Life Expectancies:
Class
Frequency
Relative
Cumulative
30-39
40-49
50-59
60-69
70-79
Do on board

46. Cumulative Relative Frequency Plot
Ogive ("oh-jive")
Adds up the percent of data you've counted as you move left to right
Shows percentile: Percent of individuals at or below a certain value
Quartile: Every 25% of the data
1st Quartile (Q1) = 25th percentile
2nd Quartile (Median) = 50th percentile
3rd Quartile (Q3) = 75th percentile
Interquartile Range (IQR) =
Example on notes outline – life expectancy in African nations
Q3 – Q1