1. Chapter 15: Statistics
Section 15.1: Formulating Statistical Questions, Gathering Data, and Using Samples

2. Statistical Questions
Statistical Questions: ones that can be answered by collecting and analyzing data (pieces of information, can be numerical or categorical)
Ex’s: (a) What is the height of each student in our class?
(b) How many home runs has each player hit in a baseball team’s
starting lineup?
(c) What on campus restaurant is the favorite among UK students?
(d) What is the average weight of watermelons sold at your local
grocery store?

3. Types of Statistical Studies
Observational Studies: observe characteristics or quantities without influencing these characteristics or quantities
Experiments: try to determine factors that influence characteristics or quantities

4. Gathering Data
The population is the full set of people or things that the study is designed to investigate.
Ex’s: (a) the students in our class, (b) the players in the starting lineup, (c) the UK student body, (d) all of the watermelons
A sample of a population consists of some collection of members of the population.
Samples need to be representative, i.e. the characteristics of the sample reflect those of the population
Ideal representative sample: random sample- every member of the population has an equal chance of being in the sample.

5. Gathering Data
Samples need to be representative, i.e. the characteristics of the sample reflect those of the population
Ideal representative sample: random sample- every member of the population has an equal chance of being in the sample.
Ex: Asking random students in the Student Center at lunchtime about their favorite on campus restaurant is not random or representative.

6. Using Samples
Ex: If a random sampling of 250 students showed that 60 students said Panda Express was their favorite on campus restaurant, about how many of UK’s 20,000 students would be expected to say that Panda Express is their favorite?

7. Section 15.2: Displaying and Interpreting Data

8. Displaying Categorical Data
Real graph: display using real objects in
graph form
Ex: using Starburst candy or wrappers
to display how many pieces there are of
each color

9. Displaying Categorical Data
Pictograph: uses icons or pictures to display the data
Ex: each small, colored
rectangle represents
a piece of candy for
each flavor in one
package of candy

10. Displaying Categorical Data
Bar Graph: uses a single rectangle for each category to display the data
Ex: the height of each bar
represents the number of
a piece of candy for each
flavor

11. Displaying Categorical Data
Double Bar Graph: each category is subdivided into 2 smaller categories
Ex: Displays median weekly
earnings broken down by race
and further subdivided by
gender.

12. Displaying Categorical Data
Pie Graph: uses a subdivided circle to show how data is partitioned into categories
Ex: Shows the percentage of
UK students that prefer that
particular on campus restaurant

13. Displaying Numerical Data
Dot Plot: a pictograph with categories being numbers or intervals and the icons being dots
Ex: The following displays the home runs hit by hitters in a baseball lineup, where the home runs hit were 12, 17, 25, 32, 24, 17, 12, 12, 8

14. Displaying Numerical Data
Ex: The following displays the home runs hit by hitters in a baseball lineup, where the home runs hit were 12, 17, 25, 32, 24, 17, 12, 12, 8

15. Displaying Numerical Data
Histogram: a bar graph with categories being numbers or intervals
Ex: The number of students
earning each letter grade on
an exam is displayed.

16. Displaying Numerical Data
Stem and Leaf Plot: 2 columns in which the stem (left column) and leaf (right column) together form the data
2 | 0572 = data includes 20, 25, 27, and 22
Ex: Displays the exam scores from the previous histogram 5
266 6 93 7
187827 8 9
58263

17. Displaying Numerical Data
Line Graphs: data points are plotted and adjacent points are connected by line segments, used for continuously varying data
Ex: Displays the U.S. popu-
lation each decade over the
20th century.

18. Displaying Numerical Data
Scatterplot: collection of data points in a plane, shows how 2 kinds of data are related
Ex: Compares homework
and exam averages for my
MA 201 students from last
semester

19. Reading Graphs
1. Reading the data: lift facts directly from the graphs
2. Reading between the data: use mathematical concepts and skills to compare or combine quantities and identify relationships between data
3. Reading beyond the data: predict or infer from the data

20. Section 15.3: The Center of Data: Mean, Median, and Mode

21. Motivating Example
Ex: If your 4th grade math class had the following scores on their adding fractions quiz, what score did the “average” student get?
7, 4, 9, 10, 7, 9, 9, 6
A single-number summary of a set of numerical data is called a measure of center. Ex’s are mean, median, and mode.

22. The Mean
Def: The mean (or arithmetic mean or average) of a list of numbers is calculated by adding all of the numbers and dividing that sum by the length of the list (the number of numbers).
Ex 1: The mean of the quiz scores 7, 4, 9, 10, 7, 9, 9, 6 is …

23. Visualizations of the Mean
Consider a dot plot of your numerical data as if the axis is a seesaw. The mean is the location of the fulcrum so that the seesaw is perfectly balanced.
See Activity 15K for another visual approach to finding the mean.

24. The Median
Def: The median of a list of numbers is the middle number of the list once it is ordered from smallest to largest.
Ex 2: The median of the quiz scores 7, 4, 9, 10, 7, 9, 9, 6 is …
If the length of the list is even, then take the average of the middle two numbers. If the length is odd, no average is needed.

25. See Activity 15O

26. The Mode
Def: The mode of a list of numbers is the number that occur most frequently.
Ex 3: The mode of the quiz scores 7, 4, 9, 10, 7, 9, 9, 6 is …

27. Revisiting Our Motivating Example
What score did the average or typical student get if the quiz scores were 7, 4, 9, 10, 7, 9, 9, 6?
7.625, 8, or 9 are all reasonable answers

28. Categorical Data
Def: The modal category is the category listed most frequently in your categorical data.
Note that the modal category is not necessarily the “favorite” category in statistical studies like the favorite on campus restaurant question. Study voting theory for other possibilities.

29. Section 15.4: Data Distributions

30. Definition and Types
Def: Data distribution: numerical data displayed in a dot plot or histogram.
Data distributions with a long tail that extends to the right (left) of the majority of the data is skewed to the right (left).

31. Types of Data Distributions
Data distributions which have two or more peaks bimodal.

32. Types of Data Distributions
Data distributions which have or nearly have reflectional symmetry are symmetric.

33. Other statistical measures
Def: The Pth percentile of a set of numerical data is the number such that P% of the data is ≤ that number.
Def: The 1st quartile is the 25th percentile and the 3rd quartile is the 75% percentile.
What is the 50th percentile called?
The median
Ex 4: What is the 1st quartile, 3rd quartile, and 90th percentile of the following quiz scores?
3, 4, 5, 5, 5, 6, 7, 7, 7, 7, 7, 8, 8, 9, 9, 9, 9, 10, 10, 10

34. Another Graphical Display
Def: A box plot (box and whiskers plot) is a display of the lowest value, highest value, 1st and 3rd quartiles, and the median, as shown in the example below.
Ex: Draw a box plot for the quiz scores from Ex 4:
3, 4, 5, 5, 5, 6, 7, 7, 7, 7, 7, 8, 8, 9, 9, 9, 9, 10, 10, 10