This document provides an overview and introduction to statistics. It defines key statistical concepts such as data, population, sample, parameter, and statistic. It also distinguishes between descriptive and inferential statistics. Specifically, it states that statistics is the science of collecting, organizing, analyzing, and interpreting data to make decisions. A population is the entire set being studied, while a sample is a subset of the population. A parameter describes a characteristic of the entire population, while a statistic describes a characteristic of a sample. Descriptive statistics involves summarizing and displaying data, while inferential statistics involves using samples to draw conclusions about populations.

1. Ch1 Larson/Farber
1.1 An Overview of
Statistics
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2. Ch1 Larson/Farber
Objective
The Executives will Learn and Understand
The Definition of Statistics.
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3. Ch1 Larson/Farber
Consider the following

“The number of Americans with diabetes
will nearly double in the next 25 years.”
n “The NRF expects holiday sales to decline
1% versus a 3.4% drop in holiday sales
the previous year.”
n EIA projects total U.S. natural gas
consumption will decline by 2.6 percent in
2009 and increases by 0.5 percent in
2010”
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4. Ch1 Larson/Farber
What is Data

Data consists of information coming from
observations, counts, measurements or
responses.

Sometimes data is represented
graphically.
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5. Ch1 Larson/Farber 5

6. Ch1 Larson/Farber
Where does Statistics come
from

The use of Statistics dates back to census
taking to ancient Babylonia, Egypt, and
later the Roman Empire, when data were
collected about matters concerning the
state, such as births and deaths. In fact,
the word statistics is derived from the Latin
word status, meaning “state”.
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7. Ch1 Larson/Farber 7

8. Ch1 Larson/Farber
What is Statistics?
o
http://www.learner.org/courses/againstallo
dds/unitpages/unit01.html
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9. Ch1 Larson/Farber 9
Statistics is the science of
collecting, organizing,
analyzing, and interpreting
data in order to make
decisions.
What Is Statistics?

10. Ch1 Larson/Farber
Objective

The Executives will be able to distinguish
between a population and a sample.
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11. Ch1 Larson/Farber
DATA SETS

There are two types of data sets:
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12. Ch1 Larson/Farber 12
Important Terms
Population
The collection of all outcomes, responses,
measurements, or counts that are of interest.
Sample
A subset, or part, of the population.

13. Ch1 Larson/Farber 13

14. Ch1 Larson/Farber
Example 1 (page 3)

Identifying Data Sets:

In a recent survey, 1500 adults in the
United States were asked if they thught
there was solid evidence of global
warming. Eight hundred fifty-five of the
adults said yes. Identify the population
and the sample. Describe the sample data
set.
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15. Ch1 Larson/Farber
Independent Work

Try it yourself 1 for 7 min.

Partner work for 5 min.

Class discussion.
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16. Ch1 Larson/Farber
Class Discussion

Classifying a Data Set. Page 6

Exit Ticket

Independent work page 7, questions 26-
34 even.
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17. Ch1 Larson/Farber
Objective

The Executives will be able to distinguish
between a parameter and a statistic.
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18. Ch1 Larson/Farber 18
Important Terms
Parameter
A number that describes a population characteristic.
Statistic
A number that describes a sample characteristic.
Average gross income of all
people in the United States in
2002.
2002 gross income of people
from a sample of three states.

19. Ch1 Larson/Farber
EXAMPLE 2

Distinguishing Between a Parameter and
a Statistic

1. A recent survey of 200 college career
centers reported that the average starting
salary for petroleum engineering majors is
$83,121.
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20. Ch1 Larson/Farber
Things to Ponder

Why can a sample statistic differ from
sample to sample, and a population
parameter is constant for a population?
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21. Ch1 Larson/Farber
2. The 2182 students who accepted
admission offers to Northwestern
University in 2009 have an average SAT
score of 1442.
3. In a random check of a sample of retail
stores, the Food and Drug Administration
found that 34% of the stores were not
storing fish at the prper temperature.
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22. Ch1 Larson/Farber

Try it yourself 2 (pg 4) for 7 min.

Partner work for 5 min.

Class discussion.
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23. Ch1 Larson/Farber

Class review

Page 8

35-39

Exit Ticket

Page 8

40-42
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24. Ch1 Larson/Farber
Objective

The Executives will learn how to
distinguish between descriptive statistics
and inferential statistics.
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25. Ch1 Larson/Farber 25
Inferential Statistics
Two Branches of Statistics
Descriptive Statistics
Involves organizing, summarizing, and displaying
data.
Involves using sample data to draw conclusions
about a population. A basic tool in the study of
inferential statistics is probability.

26. Ch1 Larson/Farber 26

27. Ch1 Larson/Farber
Example 3 (page 5)
1. 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.
2. In a sample of Wall Street analysts, the
percentage who incorrectly forecasted
high-tech earnings in a recent year wass
44%.
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28. Ch1 Larson/Farber

Try it yourself 3 (pg 5) for 7 min.

Partner work for 5 min.

Class discussion.
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29. Ch1 Larson/Farber
Review
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30. Ch1 Larson/Farber
Class practice
Page 8 43-44
Page 29
Exercise 3/9, 4/10
Exit Ticket
Page 8
Question 46 30