STA 205 Lecture Notes - Lecture 2: Simple Random Sample, Categorical Variable, Convenience Sampling

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19 Dec 2018
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Packet 2: Introductory Definitions Textbook pages: 1 8; 267 277 (selected topics)
After completing this material, you should be able to:
discuss what statistics is and how it can be applied to specific examples.
identify the population, sample, and what a statistical inference is for a specific example.
identify statistics that are calculated for a specific example.
identify the variable recorded for a specific example and classify the variable as categorical or quantitative.
identify the sample selected and determine if the sample is a simple random sample, a convenience sample, or a
voluntary response sample
How can we define statistics?
2 broad areas of statistics:
1.
2.
What exactly is data and why is it so important?
Data is collected when characteristics are recorded about each individual these are referred to as variables. There are
two types of variables:
1.
2.
In the space below, list several examples of categorical and quantitative variables:
Knowing what type of variable is
measured will prove to be very
important the type of variable
determines how the variable can be
summarized, as well as what type of
inference can be conducted.
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the science of reasoning from data
DESCRIPTIVE
INFERENTIAL
DATA is acollection of variables recorded for
aset of observational units
CATEGORIAL
Quantitative
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1DESCRIPTIVE Used to summarize and
describe data using graphical and
numerical techniques
2INFERENTIAL methods used to make
generalizations and draw
conclusions about alarger group
based on data from asubset of that
larger group
VARIABLE any characteristic of aperson
or thing that can be assigned acategory
or number
OBVARS.at oNaLUNIt the person or thing
to which avariable is assigned
the data we will consider has VARIABILITY
that is avariable will take on
different values from observational unit
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11 CATEGORICAL avariable which
classifies observational units into
categories
2QUANTITATIVE avariable which
means anumerical avanity
wunits for each observational
unit
VARIABLES
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