Transcript Chapter 1

© 2012 McGraw-Hill
Ryerson Limited
© 2009 McGraw-Hill Ryerson Limited
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Lind
Marchal
Wathen
Waite
© 2012 McGraw-Hill Ryerson Limited
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Learning Objectives
LO 1 Explain why we study statistics.
LO 2 Explain what is meant by descriptive statistics
and inferential statistics.
LO 3 Distinguish between a qualitative variable and a
quantitative variable.
LO 4 Describe how a discrete variable is different from
a continuous variable.
LO 5 Distinguish among the nominal, ordinal, interval,
and ratio levels of measurement.
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LO
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Why Study Statistics?
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Why Study Statistics?
Three main reasons:
1. Data are everywhere.
2. Statistical techniques are used to make many
decisions that affect our lives.
3. No matter what your career, you will make decisions
that involve data.
An understanding of statistical methods will help you make
these decisions more effectively.
LO 1
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What Is Meant By Statistics?
Statistics is the science of collecting, organizing,
presenting, analyzing, and interpreting data to assist in
making more effective decisions.
LO 1
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LO
2
Types of Statistics
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Types of Statistics
Descriptive Statistics
Methods of organizing, summarizing, and presenting data
in an informative way.
1.
2.
3.
4.
5.
LO 2
Frequency distributions
Chart forms
Central tendency
Measures
Data clustering
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Types of Statistics
Inferential Statistics
The methods used to determine something about a
population, based on a sample:
1. A population is the entire set of individuals or objects
of interest or the measurements obtained from all
individuals or objects of interest.
2. A sample is a portion, or part, of the population of
interest.
LO 2
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Types of Statistics
1. Prohibitive cost of surveying the whole population
2. Destructive nature of some tests
3. Physical impossibility of capturing the population
LO 2
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Types of Statistics
Descriptive Statistics:
1. Population census data
2. Weekly earnings of hospitality workers
3. Individual responses of registered voters regarding their
choice of Prime Minister of Canada
Inferential Statistics:
1. 46% of high school students can solve fractions,
decimals, and percentages.
2. 77% of high school students can correctly total a
restaurant menu.
LO 2
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You Try It Out!
The Wooden Furniture Company asked a sample of 2564
consumers to try out a newly developed living room set in a
showroom. Of the 2564 sampled, 2126 said they would
purchase the furniture if it were marketed.
a) What should the Wooden Furniture Company report to its Board of
Directors regarding the percentage of acceptance of the living room
set?
b) Is this an example of descriptive statistics or inferential statistics?
Explain.
LO 2
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LO
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Types of Variables
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Types of Variables
Qualitative
The characteristic being
studied is non-numeric.
Quantitative
Information is reported
numerically.
Examples:
Gender, religious affiliation,
type of automobile owned,
country of birth, eye colour
Examples:
The balance in your
chequing account, the ages
of company CEOs, the life
of a battery, the number of
children in a family
LO 3
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LO
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A Discrete Variable is Different
from a Continuous Variable
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Quantitative Variables: Classifications
Discrete Variables
Can only assume certain
values and there are usually
“gaps” between values
Continuous Variables
Can assume any value
within a specified range
Examples:
Number of bedrooms in a
house, number of cars
arriving at a shopping
centre, number of students
in a statistics course section
Examples:
Tire pressure, weight of
shipment of grain, amount
of cereal in a box, duration
of a flight
LO 4
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Types of Variables
Summary of the Variable Types
LO 3
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Important Properties
Mutually Exclusive
a property of a set of categories such that an individual or
object is included in only one category
Exhaustive
a property of a set of categories such that each individual
or object must appear in at least one category
LO 3
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LO
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Level of Measurement
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Levels of Measurement
Nominal
The variable of interest is divided into mutually exclusive
categories or outcomes. There is no natural order to the
outcomes.
Examples: colour of M&Ms, gender
Ordinal
Data classifications are represented by labels or names
(high, medium, low) that are mutually exclusive. Data
classifications are ranked or ordered according to the
particular trait they possess.
Examples: professor ratings, terrorist attack risk levels
LO 5
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Levels of Measurement
Interval
Data classifications are mutually exclusive and exhaustive.
Data classifications are ordered according to the amount of
the characteristic they possess.
Equal differences in the characteristic are represented by
equal differences in the measurement.
Examples: temperature, shoe size, IQ scores
LO 5
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Levels of Measurement
Ratio
Data classifications are mutually exclusive and exhaustive.
Data classifications are ordered according to the amount of
the characteristics they possess.
Equal differences in the characteristic are represented by
equal differences in the numbers assigned to the
classifications.
The zero point is the absence of the characteristic and the
ratio between two numbers is meaningful.
Examples: wages, weight, height
LO 5
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Levels of Data
Levels of Measurement:
Summary of Major
Characteristics
LO 5
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You Try It Out!
What level of measurement is reflected in the following
data?
a) A sample number of books read in a year by 50 readers is given
below:
15
4
3
11
17
3
1
7
14
14
10
6
6
10
18
13
4
17
16
11
5
13
8
16
9
4
5
18
16
12
7
11
9
14
11
12
5
12
17
13
8
12
12
6
2
1
6
13
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b) In a survey of 300 television viewers, 100 were from a low income
group, 150 from a middle income group, and 50 from a high income
group.
LO 5
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Ethics and Statistics
“There are three kinds of lies: lies, damn lies, and
statistics”.
-- Benjamin Disraeli
“Figures don’t lie: liars figure”.
Statistics can be misused and data can be presented in
misleading ways.
LO 5
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Computer Applications
can provide accurate information in seconds
reduce the likelihood of an error
include options such as Excel, Excel add-ins (such as
Megastat), or MINITAB
LO 5
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Chapter Summary
I. Statistics is the science of collecting, organizing,
presenting, analyzing, and interpreting data to assist in
making more effective decisions.
II There are two types of statistics.
A Descriptive statistics are procedures used to
organize and summarize data.
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Chapter Summary
B Inferential statistics involve taking a sample from a
population and making estimates about a population
based on the sample results.
1. A population is an entire set of individuals or objects
of interest or the measurements obtained from all
individuals or objects of interest.
2. A sample is a part of the population.
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Chapter Summary
III There are two types of variables.
A. A qualitative variable is categorical or nonnumeric.
1. Usually we are interested in the number or percent of
the observations in each category.
2. Qualitative data are usually summarized in graphs and
bar charts.
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Chapter Summary
B. There are two types of quantitative variables and
they are usually reported numerically.
1. Discrete variables can assume only certain
values, and there are usually gaps between
values.
2. A continuous variable can assume any value
within a specified range.
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Chapter Summary
IV There are four levels of measurement.
A. With the nominal level, the data are sorted into
categories with no particular order to the categories.
B. The ordinal level of measurement presumes that one
classification is ranked higher than another.
C. The interval level of measurement has the ranking
characteristic of the ordinal level of measurement plus
the characteristic that the distance between values is
a constant size.
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Chapter Summary
D. The ratio level of measurement has all the
characteristics of the interval level, plus there is a
meaningful zero point and the ratio of two values is
meaningful.
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