# AP Statistics Unit 3

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## Description and Tags

### 43 Terms

1

random

nobody can guess the outcome before it happens. when we want things to be fair, usually some underlying set of outcomes will be equally likely (although in many games, some combinations of outcomes are more likely than others).

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2

stimulation

mimics reality by using random numbers to represent the outcomes of real events.

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3

trial

the sequence of several components representing events that we are pretending will take place

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4

response variable

trial's outcome

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5

population

the entire group of individuals or instances about whom we hope to learn

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6

sample

a representative subset of a population, examined in hope of learning about the population

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7

bias

when sampling methods either over or under emphasize some characteristic of the population

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8

randomizing

protects us from the influences of all the features of our population by making sure that, on average, the sample looks like the rest of the population.

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9

sample size

the number of individuals in the sample that is important.

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10

census

attempting to survey the entire population

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11

population parameter

mathematical measures taken from the entire population like the population mean and standard deviation

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12

representative

we want the statistics we compute from a sample to reflect the corresponding parameters accurately.

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13

randomization

the random selection of subjects used to reduce bias in either surveys or experiments

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14

sample statistics

mathematical measures taken from a sample of the population of interest like the sample mean and sample standard deviation

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15

simple random sample

abbreviated SRS, this requires that every item in the population has an equal chance to be chosen and that every possible combination of items has an equal chance to exist. No grouping can be involved.

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16

sampling frame

a list of individuals from which the sample is drawn

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17

sampling variability

Samples drawn at random generally differ one from another. Each draw of random numbers selects different people for our sample. These differences lead to different values for the variables we measure

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18

stratified random sample

population is divided into homogenous groups and then a random sample is drawn from each group

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19

cluster sample

population is split into parts or clusters usually based on geography and then entire clusters are selected randomly and sampled

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20

multistage sample

sampling schemes that combine several different sampling methods at different stages

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21

systematic sample

a sample is drawn from the population by following a systematic plan to give every object in the population an equal chance to be chosen but all possible groups can not be formed

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22

voluntary response sample

a large group of individuals is invited to respond, and those who choose to respond are counted

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23

voluntary response bias

The sample is not representative, even though every individual in the population may have been offered the chance to respond, which invalidates the survey.

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24

convenience sample

a poor way to collect a sample - do what is convenient for the surveyor, data is usually very biased

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25

undercoverage

some portion of the intended population is either unrepresented or under-represented

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26

nonresponse bias

bias created when people who are randomly selected refuse to particiapte in the sample

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27

response bias

anything in the survey design that influences the responses from the sample

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28

factor

an experimenter must identify at least one explanatory variable

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29

levels

The specific values that the experimenter chooses for a factor

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30

treatment

The combination of specific levels from all the factors that an experimental unit receives

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31

matched design

when our data values are not independent of one another and are related somehow to one subject - it is a form of blocking

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32

observational study

a study based on data where no manipulation of factors has been employed, we simply observe what has or will happen

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33

experiment

a study where there is a definite random assignment of subjects to treatments

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34

treatment

the process, intervention, etc that is applied to each subject in an experiment

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35

principles of experimental design

control, randomize, replicate, block

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36

control group

a group created the provide a basis for comparison usually either an old or placebo treatment

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37

single blind

when the subjects in an experiment do not know if they are in the treatment or control group

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38

double blind

when the subjects as well as those evaluating the result of an experiment do not know which subjects are in the treatment or control groups

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39

placebo

a fake treatment often given to the control group to help prevent the placebo effect (subjects improving by the power of suggestion)

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40

blocking

subjects or experimental units are grouped together homogeneously because of some charcteristic they have in common that is believed might effect the experiment

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41

confounding

when the results of an experiment can be determined because a variable has not be accounted for and has interferred with your results

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42

prospective study

a study where we collect data as it happens

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43

retrospective study

a study where we collect data from events that have happened in the past

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