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Stats Terminology: Definitions for Design, Description, Inference, Probability, Quizzes of Statistics

Definitions for key statistics terminology including design, description, inference, probability, variable, subject, population, sample, descriptive statistics, inferential statistics, parameter, statistic, and random sampling.

Typology: Quizzes

2012/2013

Uploaded on 01/15/2013

dashonna
dashonna 🇺🇸

23 documents

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TERM 1
Design
DEFINITION 1
Planning how to obtain data to answer the questions of
interest
TERM 2
Description
DEFINITION 2
Summarizing and analyzing the data that are obtained
TERM 3
Inference
DEFINITION 3
Making decisions and predictions based on the data for
answering the statistical question
TERM 4
probability
DEFINITION 4
Probability is a measure of how likely it is that something will
happen or that a statement is true.
TERM 5
variable
DEFINITION 5
the characteristic being measured
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Design

Planning how to obtain data to answer the questions of

interest

TERM 2

Description

DEFINITION 2

Summarizing and analyzing the data that are obtained

TERM 3

Inference

DEFINITION 3

Making decisions and predictions based on the data for

answering the statistical question

TERM 4

probability

DEFINITION 4

Probability is a measure of how likely it is that something will

happen or that a statement is true.

TERM 5

variable

DEFINITION 5

the characteristic being measured

subject

the entity that we measure in a study

TERM 7

population

DEFINITION 7

set of all subjects of interest

TERM 8

sample

DEFINITION 8

In statistics, a sample is a subset of a population. Typically,

the population is very large, making a census or a complete

enumeration of all the values in the population impractical or

impossible.

TERM 9

descriptive statistics

DEFINITION 9

methods for summarizing the collected data using graphs

and numbers (averages and percentages

TERM 10

inferential statistics

DEFINITION 10

In statistics, statistical inference is the process of drawing

conclusions from data that is subject to random variation, for

example, observational errors or sampling variation.