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1

categorical variables

places an individual into one of several groups or categories.

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2

quantitative variables

takes numerical values for which it makes sense to find an average.

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3

distribution

tells us what values the variable takes and how often it takes these values; pattern of variation.

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4

data table

lists individuals.

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5

frequency table

summarizes distribution in counts.

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6

relative frequency table

summarizes distribution in percents.

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7

two-way table

a table used to describe two categorical variables.

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8

marginal distribution

the distribution of values of a categorical variable among all individuals described by the table.

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9

conditional distribution

describes values of variable among individuals who have a specific value of another variable; there is a different conditional distribution for each value of the other variable.

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10

segmented bar graph

a "stacked" bar graph that shows parts of a whole; forces us to use percents, easy to compare.

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11

association

high/low amounts of V1 associated with high/low amounts of V2.

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12

characteristics to address when describing the distribution of a quantitative variable

shape

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13

outliers

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14

center

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15

spread

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16

shape

skewness, symmetry

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17

center

mean, median

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18

spread

range, standard deviation

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19

histogram

labels, equal classification widths

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20

what to do with boundary values (whole number on next bar or lower bar?)

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21

make dot plot first

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22

minimum of five bins (bars)

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23

relative frequency histogram

makes it easier to compare two distributions, especially when number of individuals is very different.

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24

x bar

mean of a sample

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25

μ

mean of a population

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26

resistant measures of center

median - YES, outliers don't affect the number of items in a set

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27

mean - NO, mean is pulled in the direction of skewness

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28

how does the shape of a distribution affect the relationship between the mean and the median?

skew right: mean > median

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29

skew left: mean < median

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30

symmetric: mean = median

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31

range

max - min

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32

not resistant measure of spread

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33

quartiles

median of observations to left and right of median

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34

IQR

Q3 - Q1

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35

resistant measure of spread

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36

outliers

Q1 - 1.5(IQR) = lower boundary

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37

Q3 + 1.5(IQR) = upper boundary

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38

five-number summary

minimum, Q1, median, Q3, maximum -> boxplot

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39

standard deviation

the typical distance of the values in the data set from the mean.

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40

(dispersion, spread, variation)

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41

similarities between range, IQR, standard deviation

all measure spread

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42

differences between range, IQR, standard deviation

range is least resistant to outliers

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43

standard deviation is slightly resistant

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44

IQR is most resistant

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45

properties of standard deviation

measures spread about the mean; only use when mean is chosen as center.

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46

Sx is always greater than or equal to 0.

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47

Sx has the same measurement units as data (original observations).

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48

Sx is NOT resistant.

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49

factors to consider when choosing summary statistics

center and spread of distribution

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50

skewed/outlier: median, IQR (resistant)

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51

symmetric data without outliers: mean, standard deviation

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52

always graph for shape (histogram)

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53

four-part question

State the question.

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54

Plan (set up).

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55

Do (calculate).

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56

Conclude (in context).

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