LECTURE 9
Random Sampling and Point Estimation
This lecture covers material on Simple Random Sampling for finite and
infinite populations, and Point Estimation. Microsoft Excel is used for
some applications.
Read:
Chapter 7, Sections 7.1 through 7.3.
1
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This lecture introduces the idea of statistical inference, an important
reason for managers to use statistics.
Before we start our discussion, are a
few terms that we need to revisit and explain. They are:
Population:
The set of all elements of interest in a particular study.
The number of
elements in the population is denoted by the letter
N.
For example, the population of software designers includes all those who
work in the software design area. It might be interesting to find out some
information about software designers, such as the distribution of their
salaries, their mean or average annual salary and the standard deviation of
salaries.
When we calculate the values of the population such as the mean
or the variance, those values are called
parameters
.
The mean of a
population variable is denoted by
μ
and the standard deviation is denoted
by
σ
.
If we could contact all software designers and ask them their salaries, we
would be able to determine the distribution of salaries.
We could plot the
salaries in a frequency plot showing how many software designers got a
certain salary amount.
The distribution might be bimodal, having a lot of
software designers with high salaries and another large group with low
salaries, and a few with average salaries.
Or the distribution might be
normal, with the plot of salaries resembling a bellshaped curve.
In any
case, whatever the distribution looks like, we would call it the population
distribution.
However there is a problem in doing this.
It is not really likely that we
would be able to ask all software designers their salaries.
What we would
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 Summer '08
 SINGER
 Standard Deviation, Variance, software designers

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