Stats exam one vocab

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46 Terms

1

Individual

objects described by a set of data (could be a animal, person, or thing)

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2

Variable

any characteristic of a individual

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3

what are the two types of variables?

Numerical and Categorical

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4

Discrete (Numerical)

Not able to take all possible real numbers in a reasonable range

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5

Continuous (Numerical)

Able to take all possible real numbers in a reasonable range

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6

Categorical

any variable that is not numerical

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7

Nominal (categorical)

no real value in the order of categories

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8

Ordinal (categorical)

There is meaningful order among the categories

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9

What graphs are used for categorical variables?

bar graphs and pie charts

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10

What graphs are used for numerical variables?

Stem leaf plot and histrogram

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11

How to find mean

add up all the numbers, then divide by how many numbers there are

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12

Median

The midpoint of distribution, it is the sample size plus 1 divided by two

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13

Is mean or median resistant?

The median is resistant because it will be the same no matter what. The mean is NOT resistant because it will change based on the numbers in the value set

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14

Is standard deviation resistant?

The standard deviation is NOT resistant

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15

First quartile

the median of the lower half of the data set

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16

Third quartile

the median of the upper half of the data set

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17

5 number summary

min, Q1, median, Q3, max

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18

Are quartiles resistant measures?

Quartiles are resistant

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19

Inner Quartile Range (IQR)

the distance between Q1 and Q3. To find it subtract Q3-Q1

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20

1.5 IQR rule

used for identifying outliers: any values that are more than 1.5 times the IQR lower than the first quartile or higher than the third quartile are called outliers

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21

Scatterplot

a graphed cluster of dots, each of which represents the values of two variables

Explanatory variables go on the X axis and Response variables go on the Y axis

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22

What does correlation (r) measure?

Correlation measures the degree of relationship between two or more variables

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23

what does r tell us?

Whether there is a linear relationship between two variables, what direction the relationship is (positive or negative), and how strong the relationship is.

R is not resistant
R is not affected in the changing of number of units

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24

Population

the entire group of individuals we want to know about

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25

Sample

a part of the population we actually collect information from

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26

Parameter

a number that describes the population

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27

Statistic

A number that can be computed from sample data without using any unknown parameters

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28

Sampling design

describes exactly how to choose a sample from the population

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29

Bias

the design of a statistical study is biased if it systematically favors a outcome

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30

Convince sample

easy to reach

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31

Voluntary response sample

voluntary by individual

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32

simple random sample

n individual from a population chosen in a way so that every set of n individuals has an equal an equal chance of the sample n being selected

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33

Inference

A conclusion reached on the basis of evidence and reasoning

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34

Observational study

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

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35

Experiment

deliberately oppose some type of treatment on individuals to influence their response

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36

Response variable

measures an outcome of a study

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37

explanatory variable

A variable that helps explain or influences changes in a response variable.

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38

Terms for experiments

subjects, factors, treatments, statistical significance

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39

Subjects

individuals studied in an experiment

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40

Factors

explanatory variables of experiments

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41

treatments

any specific experimental condition applied to the subjects

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42

Random

if individual outcomes are uncertain but there is nonetheless a regular distribution of outcomes in a large number of repetitions

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43

Probability

the portion of times the outcome would occur in a very long series of reptation

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44

Sample space

the set of all possible outcomes

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45

Event

a set of outcomes, it will be a subset of the sample space

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46

Discrete vs. Continuous Variables

discrete variables will be a list in a sample space and its probabilities whereas continuous variables are on a density curve and will occur under the umbrella of a density curve

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