Chapter 1 Why Study Statistics? © Dealing with Uncertainty Everyday decisions are based on incomplete information.

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Transcript Chapter 1 Why Study Statistics? © Dealing with Uncertainty Everyday decisions are based on incomplete information.

Chapter 1
Why Study Statistics?
©
Dealing with Uncertainty
Everyday decisions are based
on incomplete information
Dealing with Uncertainty
The price of IBM stock will be
higher in six months than it is
now.
versus
The price of IBM stock is likely
to be higher in six months than it
is now.
Dealing with Uncertainty
If the federal budget deficit is as
high as predicted, interest rates will
remain high for the rest of the year.
versus
If the federal budget deficit is as
high as predicted, it is probable that
interest rates will remain high for
the rest of the year.
Sampling
Population and Sample
A population is the complete set of all items
in which an investigator is interested. A
population is the set of all of the outcomes
from a system or process that is to be
studied. N represents population size.
Examples of Populations
 Names of all registered voters in Coles
County, Illinois.
 Incomes of all families living in the
Charleston-Mattoon Area.
 Annual returns of all stocks traded on the
New York Stock Exchange.
 Grade point averages of all the students
at Eastern Illinois University.
Sampling
Population and Sample
A sample is an observed subset of
population values with sample size
given by n.
Sampling
Random Samples
Simple random sampling is a procedure
in which every possible sample of n
objects is equally likely to be chosen.
Sampling
Random Samples
Simple random sampling is a procedure
in which every possible sample of n
objects is equally likely to be chosen.
The resulting sample is usually called a
random sample.
Making Decisions
Data, Information, Knowledge
1. Data: specific observations of measured
numbers.
2. Information: processed and summarized data
yielding facts and ideas.
3. Knowledge: selected and organized
information that provides understanding,
recommendations, and the basis for decisions.
Making Decisions
Descriptive and Inferential Statistics
Descriptive Statistics include graphical and
numerical procedures that summarize and
process data and are used to transform
data into information.
Making Decisions
Descriptive and Inferential Statistics
Inferential Statistics provide the bases for
predictions, forecasts, and estimates that
are used to transform information to
knowledge.
The Journey to Making Decisions
Decision 
Knowledge
Experience, Theory,
Literature, Inferential
Statistics, Computers
Information
Descriptive Statistics,
Probability, Computers
Begin Here:
Identify the
Problem
Data