chap 2-1 business statistics: a decision-making approach 7 th edition chapter 2 graphs, charts, and...
TRANSCRIPT
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Chap 2-1
Business Statistics: A Decision-Making Approach
7th Edition
Chapter 2Graphs, Charts, and Tables –
Describing Your Data
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Chap 2-2
Chapter Goals
After completing this chapter, you should be able to:
Construct a frequency distribution both manually and with a computer
Construct and interpret a histogram
Create and interpret bar charts, pie charts, and stem-and-leaf diagrams
Present and interpret data in line charts and scatter diagrams
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Chapter Focus
First time trying practices using Excel Practices are simple….not strongly fun Try to be familiar with Excel
Describe data using frequency distribution and relative frequency distribution. Discrete Continuous
Present data using a chart Universal and popular way: Histogram
Chap 2-3
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Variable (Data) Types
Variable(Data)
Qualitative(Categorical)
Quantitative (Numerical)
1) Discrete 2) Continuous
Chap 2-4
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Chap 2-5
Data
Qualitative Data
Quantitative Data
Tabular Methods
Graphic Methods
Tabular Methods
Graphic Methods
1) Dot Plot2) Histogram3) Ogive4) Stem & Leaf Display5) Scatter Diagram
1) Frequency Distr.2) Relative/Percent Frequency Distr.3) Crosstabulation
Charts:1) Column2) Pie
1) Frequency Distr.2) Relative/Percent Frequency Distr.3) Cumulative Frequency Distr.4) Cumulative Relative/Percent Frequency Distr.5) Crosstabulation
Detail View
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Chap 2-6
Frequency Distribution (FD)
It is a tabulation of the values..
Each entry in the table contains the frequency or count of the occurrences of values within a particular group or interval,
and in this way the table summarizes the distribution of values in the sample.
Number of days read Frequency
0 44
1 24
2 18
3 16
4 20
5 22
6 26
7 30
Total 200
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Chap 2-7
Why Use FD?
A frequency distribution is a way to summarize data
The distribution condenses the raw data into a more useful form...
and allows for a quick visual interpretation of the data
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Chap 2-8
Frequency Distribution: Discrete Data
Discrete data: possible values are countable
Example: An advertiser asks 200 customers how many days per week they read the daily newspaper.
Number of days read Frequency
0 44
1 24
2 18
3 16
4 20
5 22
6 26
7 30
Total 200
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Chap 2-9
Relative Frequency
Relative Frequency: What proportion (%) is in each category?
Number of days read Frequency
RelativeFrequency
0 44 .22
1 24 .12
2 18 .09
3 16 .08
4 20 .10
5 22 .11
6 26 .13
7 30 .15
Total 200 1.00
.22200
44
22% of the people in the sample report that they read the newspaper 0 days per week
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Practice
Develop FD using Discreet Data Download the “SportShoes” Excel data file
from the class website Make sure to download and SAVE the data
file. See the note (ppt).
Chap 2-10
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Chap 2-11
Frequency Distribution: Continuous Data
Continuous Data: uncountable…..may take on any value in some interval
Example: A manufacturer of insulation randomly selects
20 winter days and records the daily high temperature (Temperature is a continuous variable because it could
be measured to any degree of precision desired – 98.58697 F)
24, 35, 17, 21, 24, 37, 26, 46, 58, 30,
32, 13, 12, 38, 41, 43, 44, 27, 53, 27
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Chap 2-12
Grouping Data by Classes
Sort raw data from low to high (easy using Excel):12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Find range: 58 (Max) – 12 (Min) = 46 (use for class width)
Determine number of classes: Rule of thumb: between 5 and 20 Calculation of class: follow 2^k>= n (n=20) Two to the power of four and five (in Excel: 2^4=16 and 2^5=32).
Then, take 5.
Thus, there should be 5 classes.
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Grouping Data by Classes
Compute class width: 10 (46/5 = 9.2 then round off 10)
Determine intervals:10, 20, 30, 40, 50 (Sometimes class midpoints are reported: 15, 25, 35, 45, 55 – if
calculation result is 13.5)
Construct frequency distribution count number of values in each class
Chap 2-13
W =
Largest Value - Smallest Value
Number of Classes
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Chap 2-14
Frequency Distribution
Data from low to high:
12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58
Class Frequency
10 but under 19.99 3 .15 20 but under 29.99 6 .30 30 but under 39.99 5 .25 40 but under 49.99 4 .20 50 but under 59.99 2 .10 Total 20 1.00
RelativeFrequency
Frequency Distribution
0 or 12 is also OK
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Chap 2-15
Histogram
0
3
6
5
4
2
00
1
2
3
4
5
6
7
5 15 25 36 45 55 More
Fre
qu
en
cy
Class Midpoints
Histogram based on FD
Data in ordered array:12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58
No gaps between
bars, since continuous
data
0 10 20 30 40 50 60
Class Endpoints
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Chap 2-16
Histogram
The classes or intervals are shown on the horizontal axis
frequency is measured on the vertical axis Bars of the appropriate heights can be used
to represent the number of observations within each class
Such a graph is called a histogram
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Chap 2-17
How Many Class Intervals?
Many (Narrow class intervals) may yield a very jagged distribution
with gaps from empty classes Can give a poor indication of how
frequency varies across classes
Few (Wide class intervals) may compress variation too much and
yield a blocky distribution can obscure important patterns of
variation.0
2
4
6
8
10
12
0 30 60 More
TemperatureF
req
ue
nc
y
0
0.5
1
1.5
2
2.5
3
3.5
4 8
12
16
20
24
28
32
36
40
44
48
52
56
60
Mo
re
Temperature
Fre
qu
en
cy
(X axis labels are upper class endpoints)
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Chap 2-18
General Guidelines
Number of Data Points Number of Classes
under 50 5 - 7 50 – 100 6 - 10 100 – 250 7 - 12 over 250 10 - 20
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Practice
Develop FD using continuous data Download the “Capital Credit Union” Excel
file from the class website See the note (ppt).
Chap 2-19
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Joint Frequency Distribution
What does the credit card balance distribution look like from male versus female cardholder? Conventional way: Develop F.D. and Hist. for each
gender separately Better way: joint the two variables (M/F) using joint
frequency distribution…much easier to compare two different variables
See the next slide
Chap 2-20
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Joint Frequency Distribution
Chap 2-21
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Chap 2-22
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Practice
Develop JFD and relative JFD using “Capital Credit Union” Excel file and then develop other types (i.e., charts, diagram) using “Bach, Lombard, & Wilson” Excel files
See the note (ppt).
Chap 2-23
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Chap 2-24
Ogives
An Ogive is a graph of the cumulative relative frequencies from a relative frequency distribution
Ogives are sometime shown in the same graph as a relative frequency histogram
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Chap 2-25
Ogives
12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58
Add a cumulative relative frequency column:
Class Frequency
10 but under 20 3 .15 .1520 but under 30 6 .30 .4530 but under 40 5 .25 .7040 but under 50 4 .20 .9050 but under 60 2 .10 1.00 Total 20 1.00
RelativeFrequency
Frequency Distribution
(continued)
Cumulative Relative
Frequency
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Chap 2-26
Histogram
0
1
2
3
4
5
6
7
5 15 25 36 45 55 More
Fre
qu
en
cy
Class Midpoints
Ogive Example
100
80
60
40
20
0
Cum
ulat
ive
Fre
quen
cy (
%)
/ Ogive
0 10 20 30 40 50 60
Class Endpoints
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Chap 2-27
Excel will show the Ogive graphically if the “Cumulative Percentage” option is selected in the Histogram dialog box
Ogives in Excel
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Chap 2-28
Other GraphicalPresentation Tools
Qualitative(Categorical)
Data
Bar Chart
Stem and Leaf Diagram
Pie Charts
Quantitative(Numerical)
Data
** Try the rest of them by yourself **
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Chap 2-29
Bar and Pie Charts
Bar charts and Pie charts are often used for qualitative (category) data
Height of bar or size of pie slice shows the frequency or percentage for each category
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Chap 2-30
Bar Chart Example 1
Investor's Portfolio
0 10 20 30 40 50
Stocks
Bonds
CD
Savings
Amount in $1000's
(Note that bar charts can also be displayed with vertical bars)
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Chap 2-31
Bar Chart Example 2
Newspaper readership per week
0
10
20
30
40
50
0 1 2 3 4 5 6 7
Number of days newspaper is read per week
Freu
ency
Number of days read
Frequency
0 44
1 24
2 18
3 16
4 20
5 22
6 26
7 30
Total 200
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Chap 2-32
Pie Chart Example
Percentages are rounded to the nearest percent
Current Investment Portfolio
Savings 15%
CD 14%
Bonds 29%
Stocks42%
Investment Amount PercentageType (in thousands $)
Stocks 46.5 42.27Bonds 32.0 29.09CD 15.5 14.09Savings 16.0 14.55
Total 110 100
(Variables are Qualitative)
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Chap 2-33
Tabulating and Graphing Multivariate Categorical Data
Investment in thousands of dollars
Investment Investor A Investor B Investor C Total Category
Stocks 46.5 55 27.5 129Bonds 32.0 44 19.0 95CD 15.5 20 13.5 49Savings 16.0 28 7.0 51
Total 110.0 147 67.0 324
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Chap 2-34
Tabulating and Graphing Multivariate Categorical Data
Side by side charts
Comparing Investors
0 10 20 30 40 50 60
S toc k s
B onds
CD
S avings
Inves tor A Inves tor B Inves tor C
(continued)
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Chap 2-35
Side-by-Side Chart Example Sales by quarter for three sales territories:
0
10
20
30
40
50
60
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
EastWestNorth
1st Qtr 2nd Qtr 3rd Qtr 4th QtrEast 20.4 27.4 59 20.4West 30.6 38.6 34.6 31.6North 45.9 46.9 45 43.9
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Chap 2-36
Stem and Leaf Diagram
A simple way to see distribution details from qualitative data
METHOD
1. Separate the sorted data series into leading digits (the stem) and the trailing digits (the leaves)
2. List all stems in a column from low to high
3. For each stem, list all associated leaves
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Chap 2-37
Example:
Here, use the 10’s digit for the stem unit:
Data sorted from low to high:12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58
12 is shown as
35 is shown as
Stem Leaf
1 2
3 5
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Chap 2-38
Example:
Completed Stem-and-leaf diagram:
Data in ordered array:12, 13, 17, 21, 24, 24, 26, 27, 28, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58
Stem Leaves
1 2 3 7
2 1 4 4 6 7 8
3 0 2 5 7 8
4 1 3 4 6
5 3 8
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Chap 2-39
Using other stem units
Using the 100’s digit as the stem:
Round off the 10’s digit to form the leaves
613 would become 6 1 776 would become 7 8 . . . 1224 becomes 12 2
Stem Leaf
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Chap 2-40
Line charts show values of one variable vs. time Time is traditionally shown on the horizontal axis
Scatter Diagrams show points for bivariate data one variable is measured on the vertical axis and
the other variable is measured on the horizontal axis
Line Charts and Scatter Diagrams
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Chap 2-41
Line Chart Example
U.S. Inflation Rate
0
1
2
3
4
5
6
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Infl
atio
n R
ate
(%)
YearInflation
Rate1985 3.561986 1.861987 3.651988 4.141989 4.821990 5.401991 4.211992 3.011993 2.991994 2.561995 2.831996 2.951997 2.291998 1.561999 2.212000 3.362001 2.852002 1.592003 2.272004 2.682005 3.392006 3.24
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Chap 2-42
Scatter Diagram Example
Production Volume vs. Cost per Day
0
50
100
150
200
250
0 10 20 30 40 50 60 70
Volume per Day
Cos
t per
Day
Volume per day
Cost per day
23 125
26 140
29 146
33 160
38 167
42 170
50 188
55 195
60 200
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Chap 2-43
Types of Relationships
Linear Relationships
X X
YY
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Chap 2-44
Curvilinear Relationships
X X
YY
Types of Relationships(continued)
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Chap 2-45
No Relationship
X X
YY
Types of Relationships(continued)
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Chap 2-46
Chapter Summary
Data in raw form are usually not easy to use for decision making -- Some type of organization is needed:
Table Graph
Techniques reviewed in this chapter: Frequency Distributions, Histograms, and Ogives Bar Charts and Pie Charts Stem and Leaf Diagrams Line Charts and Scatter Diagrams