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

by OC2621139

Department

StatisticsCourse Code

STA 205Professor

Brooke BuckleyLecture

2This

**preview**shows pages 1-3. to view the full**11 pages of the document.**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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