Business Statistics I Dr. Changping Wang
Chapter 1 – Introduction and Data Collection
I) What is Data?
Consist of information coming from observations, counts,
measurements, or responses.
• “People who eat three daily servings of whole grains have been
shown to reduce their risk of…stroke by 37%.” (Source: Whole
• “Seventy percent of the 1500 U.S. spinal cord injuries to minors
result from vehicle accidents, and 68 percent were not wearing a
seatbelt.” (Source: UPI)
II) What is Statistics?
The science of collecting, organizing, analyzing, and interpreting
data in order to make decisions.
III) Data Sets
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The collection of all outcomes, responses, measurements, or
counts that are of interest.
Examples: 1) All the registered voters in Canada;
2) All students registered in QMS102 at Ryerson
3) All people in Ontario who have OHIP.
A subset of the population.
Examples: 1) All the registered voters in Ontario;
2) All students in this class;
3) All people in Ryerson who have OHIP.
Example: Identifying Data Sets
In a recent survey, 1708 adults in the United States were asked if
they think global warming is a problem that requires immediate
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government action. Nine hundred thirtynine of the adults said
yes. Identify the population and the sample. Describe the data
set. (Adapted from: PewResearch Center)
• The population consists of the responses of all adults in the U.S.
• The sample consists of the responses of the 1708 adults in the
U.S. in the survey.
Parameter and Statistic
A number that describes a population characteristic.
Average age of all people in the United States.
A number that describes a sample characteristic.
Average age of people from a sample of three states
Example: Distinguish Parameter and Statistic
Decide whether the numerical value describes a population
parameter or a sample statistic.
1. A recent survey of a sample of MBAs reported that the average
salary for an MBA is more than $82,000. (Source:The Wall
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Sample statistic (the average of $82,000 is based on a subset of
2. Starting salaries for the all 667 MBA graduates from the
University of Chicago Graduate School of Business increased
8.5% from the previous year.
Population parameter (the percent increase of 8.5% is based on
all 667 graduates’ starting salaries)
IV) Branches of Statistics
1) Descriptive Statistics
Involves organizing, summarizing and displaying data.
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2) Inferential Statistics
Involves using sample data to draw conclusions about a
The course QMS102 will discuss Descriptive
Statistics, while QMS202 will discuss Inferential
Example: Descriptive and Inferential Statistics
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Decide which part of the study represents the descriptive branch
of statistics. What conclusions might be drawn from the study
using inferential statistics?
A large sample of men, aged 48, was studied for 18 years. For
unmarried men, approximately 70% were alive at age 65. For
married men, 90% were alive at age 65. (Source: The
Journal of Family Issues)
Solution: Descriptive statistics involves statements such as
“For unmarried men, approximately 70% were alive at age 65”
and “For married men, 90% were alive at 65.”
A possible inference drawn from the study is that being married is
associated with a longer life for men.
V) Data Collection
•A researcher observes and measures characteristics of interest
of part of a population.
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•Researchers observed and recorded the mouthing behavior on
nonfood objects of children up to three years old. (Source:
•A treatment is applied to part of a population and responses are
•An experiment was performed in which diabetics took cinnamon
extract daily while a control group took none. After 40 days, the
diabetics who had the cinnamon reduced their risk of heart
disease while the control group experienced no change.
(Source: Diabetes Care)
•Uses a mathematical or physical model to reproduce the
conditions of a situation or process.
•Often involves the use of computers.
•Automobile manufacturers use simulations with dummies to
study the effects of crashes on humans.
•An investigation of one or more characteristics of a population.
•Commonly done by interview, mail, or telephone.
•A survey is conducted on a sample of female physicians to
determine whether the primary reason for their career choice is
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VI) Data Classification
Types of Data
1) Qualitative Data (Categorical Data) consists of
attributes, labels, or nonnumerical entries.
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2) Quantitative data (Numerical Data)
Numerical measurements or counts.
Discrete: From a counting process.
Continuous: From a measuring process.
Levels of Measurement
Data can be classified according to the type of measurement
scale that is involved. The measurement scale (level of
measurement) is the set of all possible values that could result
when the data is collected. The type of measurement scale often
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tells which calculations can be performed and what type of
graphical display is appropriate.
Nominal level of measurement
• Qualitative data only. The categories have no particular rating,
rank or order.
• Categorized using names, labels, or qualities
• No mathematical computations can be made
Example: 1) Marital Status: single, married, divorced or
widowed: 1=single, 2=married, etc.
2) Colour of cars: blue, red, grey, silver …
3) Boarding gates: E9, F131, …
4) Gender: Male, Female
Ordinal level of measurement
• Qualitative data
• Data can be arranged in order. We may say one category is
higher or better than another.
• Differences between data entries is not meaningful
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1) Professional ranks: Lecturer=1, Assistant Prof.=2, Associate
Prof.=3, Full Prof.=4
2) Rating a product or a service: 1=Very poor, 2=Poor,
3=Average, 4=Good, 5=Excellent
3) Order of finishing in a sporting event: 1 , 2 , 3 places, …
4) Letter grades: A+, A, A, B+, B, B, …
Interval level of measurement
• Quantitative data
• Data can ordered
• Differences between data entries is meaningful
• Zero represents a position on a scale (not an inherent zero –
zero does not imply “none”)
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1) Temperature (