Created by Dane McGuckian
Statistics
Exam One Notes
Statistics
is a collection of methods for planning experiments, obtaining data, and then
organizing, summarizing, presenting, analyzing, interpreting and drawing conclusions based on
the data.
It is the science of data.
Statistical thinking
involves applying rational thought and the science of statistics to critically
assess data and inferences.
In this course we will divide our study of statistics into two categories:
Descriptive statistics,
is where we will organize and summarize the data, and…
Inferential statistics
is where we use data to make predictions and decisions about a population
based on information from a sample.
s
Descriptive statistics
utilizes numerical and graphical methods to look for patterns in a
data set, to summarize the information revealed in a data set and to present that
information in a convenient form.
s
Inferential statistics
utilizes sample data to make estimates, decisions, predictions or
other generalizations about a larger set of data.
Above, we mentioned the word population.
Let’s define two important terms used in this course:
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The
population
is the set of
all
measurements of interest to the investigator.
Typically, there are
too many experimental units in a population to consider
every
one.
However, if we can examine
every single one, we conduct what is called a
census
.
A
sample
is a subset of measurements selected from the population of interest.
Example 1: In a study of household incomes in a small town of 1000 households, one might
conceivably obtain the income of every household. However, it is probably very expensive and
time consuming to do this.
Therefore, a better approach would be to obtain the data from a
portion of the households (let’s say 125 households). In this scenario, the 1000 households are
referred to as the population and the 125 households are referred to as a sample.
A
parameter
is a numerical measurement describing some characteristic of a
population
and
computed from all of the population measurements.
For example, a population average (mean),
the average obtained from every item in the population, is a parameter.
A
statistic
is a numerical measurement describing some characteristic of a
sample
drawn from
the population.
The example below will illustrate these ideas.
One way to remember where parameters and
statistics come from is to notice that the letter P is the first letter of Population and Parameter and
S is the first letter of Sample and Statistic.
Example 2: In the household incomes example from above, the average (mean) income of all
1000 households is a parameter, whereas the average (mean) income of the 125 households is a
statistic.
Example 3
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 Winter '08
 STAFF
 Statistics, Standard Deviation, Mean, Dane McGuckian

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