MATHEMATICS Flashcards

(37 cards)

1
Q

is the study of the methods of collecting, organizing,
presenting, analyzing, and drawing conclusions about data, commonly
in numerical form.

A

STATISTIC from the Latin word staticus means out of state

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2
Q

is the branch of statistics that focuses on
collecting, summarizing, and presenting a set of data.

A

descriptive statistic

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3
Q

is the branch of statistics that analyzes sample data to draw
conclusions about a population.

A

inferential statistic

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4
Q

consists of all elements – individuals, items, or
objects – whose characteristics are being studied.

A

population

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5
Q

from a
statistical population is a proportion (a subset) of the population
selected for study.

A

sample

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6
Q

is an unorganized data gathered during the collection
stage.

A

raw data

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7
Q

is when we collect data for every member of the group
(the whole “population”).

A

census

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8
Q

A variable that cannot
assume a numerical value but can be classified into two or
more non-numeric categories

A

Qualitative or Categorical data

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9
Q

A variable that can be
measured numerically

A

quantitative or numerical data

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10
Q

Data can be collected in many ways, such as direct
observation, survey, census or sample.

A

data collection

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11
Q

There are a wide variety of ways to summarize, organize, and

present data. Most of the common methods are as follows: stem-
and-leaf diagrams, frequency distributions, histograms, bar, and

other graphs.

A

data organization

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12
Q

is a special table where each data value is
split into a “stem” (the first digit or digits) and a “leaf” (usually the
last digit). The “stem” values are listed down, and the “leaf” values
go right (or left) from the stem values.

A

stem and leaf

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13
Q

is a graphical display of data using dots.

A

dot plot

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14
Q

is a representation, either in a graphical
or tabular format, which displays the number of observations
within a given interval. The interval size depends on the data being
analysed and the goals of the analyst. The intervals must be
mutually exclusive and exhaustive.

A

frequency distribution

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15
Q

is a graphical display of
data using bars of different heights.

A

bar graph/ chart // histogram

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16
Q

a graph that shows information that is connected
in some way (such as change over time)

17
Q

a special chart that uses “pie slices” to show
relative sizes of data.

18
Q

is a way of showing data using images.

19
Q

countable

A

discrete variables

20
Q

as infinite number of value

A

continuous variables

21
Q

is a summary statistic that
represents the center point or typical value of a dataset. These
measures indicate where most values in a distribution fall and are also
referred to as the central location of a distribution.

A

central of tendency

22
Q

is the sum of measurements divided by their number.

The arithmetic average or —– is most widely used and is hence
called the ‘Common Average’ or even simply ‘Average’. It is a measure of
central value. It provides an accurate description of the sample and
indirectly, that of population.

defined as the point on the
scale of measurement obtained by dividing the sum of all the scores by
the number of scores.

23
Q

is defined as the middle value in a distribution, below
and above which lie values with equal total frequencies or probabilities

24
Q

is the single measure or score which occurs most
frequently.

25
which is also known as raw data, is data that has not been placed in any group or category after collection. Data is categorized in numbers or characteristics.
ungrouped data
26
If n is -----, then the median is the middle number.
odd
27
If n is ----, then the median is the average of the two middle number.
even
28
is the state of getting dispersed or spread.
dispersion
29
means the extent to which a numerical data is likely to vary about an average value.
statistical dispersion
30
is the difference between the largest and the smallest observation in the data.
range
31
is the most commonly used measure of dispersion. It is a measure of spread of data about the mean. SD is the square root of the sum of squared deviation from the mean divided by the number of observations. The square root of the variance is known as the standard deviation i.e.
standard deviation
32
tells the variation of the data from one another and gives a clear idea about the distribution of the data.
measure of dispersion
33
contains the same unit as the original data set. ---------- method expresses the variations in terms of the average of deviations of observations like standard or means deviations.
absolute dispersion
34
Deduct the mean from each data in the set then squaring each of them and adding each square. Finally divide them by the total number of values in the data set.
variance
35
The average of numbers is known as the mean and the arithmetic mean of the absolute deviations of the observations from a measure of central tendency is known as the mean deviation (also called mean absolute deviation).
mean and mean deviation
36
are used to compare the distribution of two or more data sets. This measure compares values without units. Common relative dispersion methods include:
relative measure of dispersion
37
are the data or scores that are arranged in a frequency distribution.
grouped data