2.2 histograms & frequency distributions for quantative data Flashcards

1
Q

frequency distribution for continuous quantitative data

A

we divide the data into class because they have no natural categories

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2
Q

classes

A

intervals of equal width that cover all values that observed in the data set

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3
Q

lower class limit

A

smallest value that appears in the class

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4
Q

upper class limit

A

largest value that can appear in the class

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5
Q

class width

A

difference between consecutive lower class limits

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6
Q

guidelines for choosing classes

A

every observation must fall into one of the classes, classes cant overlap, classes have to have equal width, there should be no gaps between classes even if there are no observations in a class, it needs to be included in the frequency districution

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7
Q

constructing a frequency distribution

A
  1. choose a class width 2. pick a lower class limit for the first class which should be a convenient # that is slightly less than the minimum data value, 3. compute the lower limit for the second class by adding the class width to the lower limit for the first class, 4. compute the lower limits for each of the remaining classes by adding the class width to the lower limit fo the preceding class. stop when the largest data value is included in a class 5. count the number of observations in each class and construct the frequency distribution
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8
Q

relative frequency distribution aka frequency distribution

A

frequency/ sum of all frequencies

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9
Q

histogram

A

a bar graph that displays the relative frequency distribution with its width equal to the class width

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10
Q

frequency vs relative frequency

A

the vertical axis for frequency is a whole number and for relative its a decimal

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11
Q

choosing the number of classes

A

not too little and not too much; too few lacks details and too much obscures the main features of the data

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12
Q

histograms on ti-84 plus

A

enter data in L1; press 2nd,Y=, then 1 to access plot 1 menu. select On and the histogram plot type; press zoom, 9 to view the plot

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13
Q

skewed to the right, or positively skewed

A

a histogram with a long right-hand tail

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14
Q

skewed to the left, or negatively skewed

A

histogram with a long left- hand tail

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15
Q

symmetric

A

if the histograms’ right have is a mirror image of its left half

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16
Q

bell-shaped

A

a symmetric histogram wth a peak in the middle

17
Q

uniformly distributed

A

a symmetric histogram in which all classes have about equal frequencies

18
Q

mode

A

a peak or high point of a histogram

19
Q

unimodal

A

has only one mode

20
Q

bimodal

A

has two clear and distinct modes