1. Organizing and Summarizing Data
Chapter 2
Organizing and Summarizing Data

2. Organizing Qualitative Data
Section
Organizing Qualitative Data
2.1

3. When data is collected from a survey or designed experiment, they must be organized into a manageable form. Data that is not organized is referred to as raw data.
Ways to Organize Data
Tables
Graphs
Numerical Summaries (Chapter 3)
A frequency distribution lists each category of data and the number of occurrences for each category of data. 3

4. EXAMPLE Organizing Qualitative Data into a Frequency Distribution
A physical therapist wants to determine types of rehabilitation required by her patients. To do so, she obtains a simple random sample of 20 of her patients and records the body part requiring rehabilitation. Construct a frequency distribution of location of injury.
Back, Wrist, Elbow, Back, Hip, Neck, Shoulder, Back, Knee , Hand, Back, Back, Back, Shoulder, Knee, Knee, Shoulder, Back, Knee, Back 4

5. Location
Tally
Frequency
Back
IIIII III 8
Wrist I 1
Elbow
Hip
Neck
Shoulder
III 3
Knee
IIII 4
Hand

6. The relative frequency is the proportion (or percent) of observations within a category and is found using the formula:
A relative frequency distribution lists each category of data with the relative frequency. 6

7. Use the frequency distribution obtained to construct a relative frequency distribution of the color of plain M&Ms.
Color
Tally
Frequency
Brown
||||| ||||| || 12
Yellow
||||| ||||| 10
Red
||||| |||| 9
Orange
||||| | 6
Blue
||| 3
Green
||||| 5 7

8. Color Tally Frequency Relative Frequency Brown ||||| ||||| || 12
||||| ||||| || 12
12/45 ≈
Yellow
||||| ||||| 10
0.2222
Red
||||| |||| 9
0.2
Orange
||||| | 6
0.1333
Blue
||| 3
0.0667
Green
||||| 5
0.1111 8

9. EXAMPLE. Organizing Qualitative Data into a Relative
EXAMPLE Organizing Qualitative Data into a Relative Frequency Distribution
Use the frequency distribution obtained in the prior example to construct a relative frequency distribution of the location of injury. 9

10. Location
Tally
Frequency
Relative Frequency
Back
IIIII III 8
8/20 = 0.4
Wrist I 1
0.05
Elbow
Hip
Neck
Shoulder
III 3
0.15
Knee
IIII 4
0.2
Hand

11. Bar Graphs
A bar graph is constructed by labeling each category of data on either the horizontal or vertical axis and the frequency or relative frequency of the category on the other axis. Rectangles of equal width are drawn for each category. The height of each rectangle represents the category’s frequency or relative frequency.

12. Construct a bar graph
Frequency table

13. 2.1 Organizing Qualitative Data 2.1.2 Construct Bar Graphs (4 of 13)

14. Organizing Quantitative Data: The Popular Displays
Section
Organizing Quantitative Data: The Popular Displays
2.2

15. EXAMPLE. Constructing Frequency and Relative
EXAMPLE Constructing Frequency and Relative Frequency Distribution from Discrete Data
The following data represent the number of available cars in a household based on a random sample of 50 households. Construct a frequency and relative frequency distribution.
Data based on results reported by the United States Bureau of the Census. 15

16. ||||| ||||| ||||| ||||| || 22 0.44
# of Cars
Tally
Frequency
Relative Frequency
|||| 4
4/50 = 0.08 1
||||| ||||| ||| 13
13/50 = 0.26 2
||||| ||||| ||||| ||||| || 22
0.44 3
||||| || 7
0.14
|||
0.06 5 |
0.02 16

17. A histogram is constructed by drawing rectangles for each class of data. The height of each rectangle is the frequency or relative frequency of the class. The width of each rectangle is the same and the rectangles touch each other.
(Note: can also be thought of as bar graph) 17

18. EXAMPLE Drawing a Histogram for Discrete Data
Draw a frequency and relative frequency histogram for the “number of cars per household” data.
# of Cars
Frequency
Relative Frequency 4
4/50 = 0.08 1 13
13/50 = 0.26 2 22
0.44 3 7
0.14
0.06 5
0.02 18

19. 19

20. 20

21. Classes are categories into which data are grouped
Classes are categories into which data are grouped. When a data set consists of a large number of different discrete data values or when a data set consists of continuous data, we must create classes by using intervals of numbers. 21

22. The following data represents the number of persons aged 25 - 64 who are currently work-disabled.
The lower class limit of a class is the smallest value within the class while the upper class limit of a class is the largest value within the class. The lower class limit of first class is 25. The lower class limit of the second class is 35. The upper class limit of the first class is 34. The class width is the difference between consecutive lower class limits. The class width of the data given above is 35 – 25 = 10. 22

23. EXAMPLE. Organizing Continuous Data into a
EXAMPLE Organizing Continuous Data into a Frequency and Relative Frequency Distribution
The following data represent the time between eruptions (in seconds) for a random sample of 45 eruptions at the Old Faithful Geyser in Wyoming. Construct a frequency and relative frequency distribution of the data.
Source: Ladonna Hansen, Park Curator 23

24. The smallest data value is 672 and the largest data value is 738
The smallest data value is 672 and the largest data value is We will create the classes so that the lower class limit of the first class is 670 and the class width is 10 and obtain the following classes: 24

25. Time between Eruptions (seconds) Tally Frequency Relative Frequency
670 – 679 || 2
2/45 = 0.044
||||| || 7
0.1556
||||| |||| 9
0.2
||||| ||||| | 11
0.2444 25

26. The choices of the lower class limit of the first class and the class width were rather arbitrary.
There is not one correct frequency distribution for a particular set of data.
However, some frequency distributions can better illustrate patterns within the data than others. So constructing frequency distributions is somewhat of an art form.
Use the distribution that seems to provide the best overall summary of the data. 26

27. Time between Eruptions (seconds)
Tally
Frequency
Relative Frequency
670 – 674 | 1
1/45 =
0.0222
||||| || 7
0.1556 || 2
0.0444
||||| 5
0.1111
|||| 4
0.0889
||||| | 6
0.1333
0.1114
||| 3
0.0667 27

28. Choosing the Lower Class Limit of the First Class
Guidelines for Determining the Lower Class Limit of the First Class and Class Width
Choosing the Lower Class Limit of the First Class
Choose the smallest observation in the data set or a convenient number slightly lower than the smallest observation in the data set. 28

29. Determining the Class Width
Decide on the number of classes. Generally, there should be between 5 and 20 classes. The smaller the data set, the fewer classes you should have.
Determine the class width by computing
Round this value up to a convenient number. 29

30. EXAMPLE. Constructing a Frequency and Relative
EXAMPLE Constructing a Frequency and Relative Frequency Histogram for Continuous Data
Using class width of 10: 30

31. Relative Frequency 31

32. Using class width of 5: 32

33. Uniform distribution the frequency of each value of the variable is evenly spread out across the values of the variable
Bell-shaped distribution the highest frequency occurs in the middle and frequencies tail off to the left and right of the middle
Skewed right the tail to the right of the peak is longer than the tail to the left of the peak
Skewed left the tail to the left of the peak is longer than the tail to the right of the peak. 33

34. 34

35. EXAMPLE Identifying the Shape of the Distribution
Identify the shape of the following histograms which represents the time between eruptions at Old Faithful. 35

36. Skewed Right
Skewed Left
Skewed Left (slightly)
Bell Shaped