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1

Population

A statistical study of the entire group of individuals we want information about

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2

Census

Collects data from every individual in the population

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3

Sample

A set of individuals in the population from which we collect data

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4

Sample Survey

A study that collects data from a sample to learn about the population from which sample was selected

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5

Convenience sampling

Selects individuals from the population that are easy to reach

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6

Bias

The design of a statistical study

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7

Volunteer response sampling

Allows people to choose to be in the sample by responding to a general invitation

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8

Random

Involves using a chance to process to determine are included in the sample

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9

Sampling without replacement

An individual from a population can be selected only once

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10

Sampling with replacement

An individual from a population can be selected more than once

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11

Simple Random Sample (SRS)

Of size N is chosen in such a way that every group of N individuals in the population has an equal chance to be selected

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12

Strata

Groups of individuals in a population who share characteristics thought to be associated with the variables being measured

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13

Sampling

Selects a sample by choosing an SRS from each stratum and combining the SRS’s into one overall sample

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14

Cluster

A group of individuals in the population that are located near eachother

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15

Cluster Sampling

Selects a sample by randomly choosing clusters and including each member of the selected cluster

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16

Systematic Random Sampling

Selects a sample from an ordered arrangement of the population by randomly selecting one of the first individuals and choosing every individual thereafter.

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17

Undercoverage

Occurs when some members of the population are less likely to be chosen or cannot be chosen in a simple

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18

Nonresponse

Occurs when an individual chosen for the sample can’t be connected or refuses to participate

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19

Response Bias

Occurs when a systemic pattern of inaccurate answers to a survey question

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20

Observational Study

Observes individuals and measures variables of interest but does not attempt to influence the responses

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21

Response variable

Measures an outcome of a study

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22

Explanatory variable

May help explain or predict changes in response variable

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23

Experiment

An experiment deliberately imposes treatments (conditions) on individuals to measure their responses

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24

Placebo

A treatment that has no active ingredient, but is otherwise like other treatment

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25

Treatment

A specific condition applied to the individuals in any experiment

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26

Experimental Units

The object to which a treatment is randomly assigned

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27

Subjects

When the experiment units are human beings

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28

Factor levels

In an experiment, a factor is an explanatory variable that is manipulated and may cause a change in the response variable. The different are called levels.

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29

Control Group

Used to provide a baseline for comparing the effects of other treatments.

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30

Placebo Effect

Describes the fact that some subject in an experiment will respond favorably to any treatment even an inactive

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31

Double-blind

Neither the subjects nor those who interact with them and measure the response variable know which treatment a subject is receiving

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32

Single-blind

Either subjects or the people who interact with them and measure the response variable don’t know which treatment a subject is receiving

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33

Random Assignment

A random assignment means that the experimental units are assigned to treatments using a chance process

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34

Control

Means keeping other variables constant for all experimental wins

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35

Replication

Giving enough treatment to enough experiment units

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36

Confounding

Occurs when two variables are associated in such way that their effects on a response variable cannot be distinguished from each other

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37

Completely Randomized Design

The experimental units are assigned to the treatments completely at random

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38

Block

A group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments.

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39

Randomized block design

Random assignment of experimental units to treatments is carried out separately within each week

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40

Matched pair design

A common experimental design for comparing two treatments that use block for size 2

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41

Retroprespective

Examine existing data for a sample of individuals

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42

Prospective

Observational studies that track individuals into the future

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43

Sampling variability

The fact that different random samples of the same size from the same population produce different estimates

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44

Statistically significant

Observed results of a study are too unusual to be explained by chance

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45

Random selection

Individuals allow inference about the population from which the individuals were chosen

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46

Random assignment

Individuals to groups allows inference about cause and effect

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