FREQUENCY DISTRIBUTION Flashcards

(61 cards)

1
Q

is a graphical technique that
organizes data into a histogram-like display.

A

STEM PLOTS

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2
Q

It is an excellent way to begin an analysis and is a good way to learn several important statistical principles.

A

steam-and-leaf plot (stem plot)

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3
Q

components of setm and leaf plot

A

Stem

Leaf

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4
Q

Three aspects of the distribution are
now visible:

A

Shape

Location

Spread

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5
Q

refers to the configuration of data points as they
appear on the graph.

A

Shape

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6
Q

This is seen as a ’skyline silhouette’.

A

Shape

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7
Q

A distribution’s shape can be discussed in terms
of its

A

Symmetry

modality

kurtosis

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8
Q

refers to the degree to which the
shape reflects a mirror image of itself around
it center.

A

Symmetry

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9
Q

is a measurement of the
distortion of symmetrical distribution or
asymmetry in a data set.

A

Skewness

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10
Q

refers to the number of
peaks on the distribution.

A

Modality

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11
Q

3 kinds of modality

A

unimodal
bimodal
multimodal

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12
Q

refers to the steepness of the mound.

A

Kurtosis

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13
Q

3 kinds of kurtosis

A

mesokutric curve
leptokurtic curve
platykurtic curve

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14
Q

Distributions that are moderate in breadth and curves with a medium peaked height.

A

Mesokurtic:

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15
Q

More values in the distribution tails and more values close to the mean (i.e. sharply peaked
with heavy tails)

A

Leptokurtic:

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16
Q

Fewer values in the tails and fewer values close to the mean

A

Platykurtic:

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17
Q

the curve has a flat peak and
has more dispersed scores with lighter tails

A

Platykurtic:

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18
Q

sharply peaked
with heavy tails

A

Leptokurtic

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19
Q

refers to the center of a
distribution.

A

average

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20
Q

two different ways to identify a
distribution’s average

A

arithmetic average
median

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21
Q

is a distribution’s
gravitational center.

A

arithmetic average

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22
Q

is the point that divides the
data set into a top half and bottom half

A

median

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23
Q

has a depth of (n +1)/ 2

A

median

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24
Q

is the sample size

A

n

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25
When n is even, the median will fall between
2 values
26
is an informal way to refer to the dispersion or variability of data points
Spread
27
3 Measures of Variation
Range (highest - lowest) Standard Deviation Variance
28
tables are a traditional way to describe the distribution of counts in a data set.
Frequency
29
Three types of frequencies
frequency column relative frequency cumulative frequency
30
column that contains counts
frequency
31
column contains frequency counts divided by the total with values expressed as a percentage
relative frequency
32
column contains precents that fall within or below a given level
cumulative frequency
33
is one which can take only isolated values
discrete variable
34
Normally, it does not carry any fractional value. Usually it is the result of counting something
discrete variable
35
is also called a discontinuous variable
discrete variable
36
is capable of assuming any fractional value within a specified range of values.
continuous variable
37
It is the result of measuring something.
continuous variable
38
2 Class-limits
lower limit upper limit
39
the smallest possible measurement in a class is known as lower limit
lower limit
40
the highest possible measurement
upper limit
41
is the point lying halfway between the lower limit and the upper limit.
Mid-point of a Class Interval
42
mid point formula
(L + U) / 2
43
meaning of L in midpoint formula
lower limit
44
# * meaning of U in midpoint formula
upper limit
45
means the difference between the upper limit and lower limit of a class interval.
magnitude of a class interval
46
Two types of classification according to the class-intervals
exclusive method inclusive method
47
in this method the upper limit of a class becomes the lower limit of the next class.
exclusive method
48
in this method we do not put any item that is equal to the upper limit of a class in the same class but we put it in the next class
exclusive method
49
here, the upper limits of classes are excluded from them
exclusive method
50
in this method the upper limimt of any class interval is kept in the same class-interval
Inclusive method
51
in this method the upper limit of a previous class is less by 1 from the lower limit of the next class interval.
inclusive method
52
this method allows a class-interval to include both its lower and upper limits within it
inclusive method
53
4 kinds of frequency charts
Bar charts Histograms Frequency Polygon Pie charts
54
is a good choice when you want to compare the frequencies of different values. It’s much easier to compare the heights of bars than the angles of pie chart slices.
bar chart
55
2 types of bar graphs
horizontal bar graphs and vertical bar graphs
56
horizontal bar graphs and vertical bar graphs
bar graphs
57
the bars are placed continuously side by side without a gap between consecutive bars.
Histograms
58
is a line graph of class frequency plotted against class midpoint
frequency polygon
59
It can be obtained by joining the midpoints of the tops of the rectangles in the histogram
frequency polygon
60
is a circle that’s divided into one slice for each value.
pie chart
61
in pie charts, the size of the slices shows their ----
relative frequency