Chapter 2 - Describing Location in a Distribution Flashcards

0
Q

add the counts in the frequency column for the current class and all classes with smaller values of the variable

A

cumulative frequency column

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1
Q

value with p percent of the observations less than it

A

pth percentile

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2
Q

divide the entries in the cumulative frequency column by the total number of individuals. multiply by 100 to convert to a percent

A

cumulative relative frequency column

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3
Q

divide the count in each class by the total number of individuals. multiply by 100 to concert to a percent

A

relative frequency column

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4
Q

plot a point corresponding to the cumulative relative frequency in each class at the smallest value of the next class

A

cumulative relative frequency graph

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5
Q

standardized score when x is an observation from a distribution that has known mean and standard deviation find the

A

z score

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6
Q

subtracting the same positive number from each value in a data set shifts the distribution to the left by that number

A

effect of subtracting a constant

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7
Q

shift the distribution to the right by that constant

A

effect of adding a constant

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8
Q
  • multiples or divides measures of center and location (mean, median, quartiles, percentiles) by b
  • multiples or divides measures of spread (range, iqr, sx) by b
  • does not change shape of distribution
A

effect of multiplying or dividing by a constant

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9
Q
  • always on or above the horizontal axis
  • has area of exactly 1 underneath it

describes overall pattern of distribution.

A

density curve

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10
Q

“equal areas point” where half the area under the curve is to It’s left and the remaining half of the area to It’s right

A

median of a density curve

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11
Q

“balance point” of a distribution

-pulled away from median in the direction of the long tail

A

mean of a density curve

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12
Q

the ____ and ____ of a symmetric density curve are equal

A

mean and median

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13
Q

used to represent standard deviation of a density curve

A

o greek letter sigma

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14
Q

changing mew without changing o moves the normal curve along the horizontal axis without

A

changing it’s spread

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15
Q

standard deviation o controls the spread of a

A

normal curve

16
Q

point at which this change of curvature takes place are located at a distance o on either side of mean mew

A

locating o by eye on a normal curve

17
Q
  • described by a normal density curve

- specified by mean mew and sx o

A

normal distribution

18
Q
  • where the mean of a normal distribution can be found at the center in a symmetric distribution
  • sx is distance from the center to the change of curvature points on either side
  • symmetric, single peak, bell shaped
A

normal curve

19
Q
  • applies only to norma distributions
  • approximately 68% of observations fall within o and mean mew (middle of curve)
  • approximately 95% of observations fall within 2o and mean mew
  • approximately 99.7% of observations fall within 3o and mean mew (outers of curve)
A

68-95-99.7 rule

use mew +/- n(o)

20
Q

-in any distribution, the proportion of observations falling within k standard deviations of the mean is at least 1- (1/ksquared)

A

chebyshevs inequality

21
Q
  • normal distribution with mean 0 and sx 1

- if variable x has any normal distribution N(mew, o) with mean mew and sx o, you must

A

standardize the variable

z=(x-mew)/o

22
Q
  • table of areas under the standard normal curve
  • table entry for each value z is the area under the curve to the left of z for less than problems
  • table entry for each value z is the area under the curve to the right of z for greater than
A

standard normal table

23
Q
  • state distribution and the values of interest: draw a normal curve with the area of interest shaded and the mean, sx, and boundary values identified
  • either a) computer z score for each boundary value and use table a or technology or b) use the normalcdf command and label each of the inputs
A

how to find the area in any normal distribution

24
- draw normal curve with the area of interest shaded and the mean, sx, and unknown boundary identified - either a) use table a or technology to find value of z with the indicated area under the standard normal curve, then unstandardize to transform back to original distribution or b) use the invnorm command and label each input
finding values from areas in any normal distribution
25
a graph is not normal when
- data is clearly skewed - has multiple peaks - isn't bell shaped
26
provides a good assessment of whether a data set follows a normal distribution
normal probability plot
27
how interpret a normal probability plot
- if points on normal probability plot lie close to a straight line, plot indicates the data is normal - systematic deviations from a straight line indicate a non normal distribution - outliers appear as points that are far away from the overall pattern of the plot
28
right skewed distribution in a normal probability plot
largest observations fall distinctly to the right of a line drawn through the main body of points
29
left skewed distributiocin a normal probability plot
largest observations fall distinctly to the left of a line drawn through the main body of points