Chapter 1 Exploring Data Flashcards

1
Q

individuals

A

objects described in a set of data, can be people, animals, things, etc

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2
Q

variable

A

any characteristic of an individual, they can take different values for different individuals

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3
Q

categorical variable

A

places an individual into one of several groups of categories

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4
Q

quantitative variable

A

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

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5
Q

distribution

A

tells us what values the variable takes and how often it takes these values

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6
Q

pie charts and bar graphs

A

can be used to display the distribution of a categorical variable more clearly

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7
Q

marginal distribution of one of the categorical variables in two way table

A

distribution of the values of that variable among all individuals described in the table

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8
Q

conditional distribution of a variable

A

describes the values of that variable among individuals who have specific value of an other variable

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9
Q

association

A

occurs in two variables if specific values of one variable tend to occur in common with specific values of the other

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10
Q

Simpson’s paradox

A

an association between two variables that holds for each individual value of a third variable can be changed or reversed when the data for all values of the third variable are combined

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11
Q

roughly symmetric: within a distribution

A

if the right & left sides of the graph are approximately mirror images of each other

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12
Q

skewed to the right: within a distribution

A

if the right side of the graph (containing half of the observations with larger values) is much longer than the left side.

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13
Q

skewed to the left: within a distribution

A

if the left side of the graph is much longer than the right side

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14
Q

median M

A

midpoint of the distribution, the number that half the observations are smaller and the other half are larger

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15
Q

steps for find the median (M)

A
  1. arrange all observations in order of size, from smallest to largest. 2. if the number of observations n is off, the median M is the center observation in the ordered list. 3. if the number of observations n is even, the median M is the average of the two center observations in the ordered list
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16
Q

the 1.5 X IQR rule for outliers

A

an observation can be considered an outlier if it falls either more than 1.5 X IQR above the third quartile or 1.5 X IQR below the first quartile

17
Q

standard deviation

A

measures the average distance of the observations to the mean

18
Q

how to calculate the standard deviation

A

find the average of the squared distances and then taking the squared root

19
Q

variance

A

average squared distance to the mean