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Applied Statistics > M3 > Flashcards

M3 Flashcards

1
Q

Information obtained by observing values of a variable is called

A

raw data.

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2
Q

Data obtained by observing values of a qualitative variable are
referred to as

A

qualitative data.

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3
Q

Data obtained by observing values of a quantitative variable are
referred to as

A

quantitative data.

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4
Q

Quantitative data obtained from a discrete variable are also

referred to as

A

discrete data

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5
Q

quantitative data obtained

from a continuous variable are called

A

continuous data.

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6
Q

Data can be classified as

A

grouped or ungrouped data.

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7
Q

are data that are not organized, or if arranged,

could only be from highest to lowest or lowest to highest.

A

Ungrouped data

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8
Q

are data that are organized and arranged into

different classes or categories.

A

Grouped data

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9
Q

can be presented in textual form, as in

paragraph form.

A

Ungrouped data

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10
Q

This involves enumerating the important
characteristics, giving emphasis on significant figures and
identifying important features of the data.

A

textual form

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11
Q

tables. By organizing the data in
X, important features about the data can be readily understood and
comparisons are easily made

A

tables

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12
Q

consists of the table number and the title

A

Table Heading :

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13
Q

It describes the data in each column.

A

Column Header :

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14
Q

It shows the classes or categories.

A

Row Classifier :

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15
Q

This is the main part of the table.

A

Body :

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16
Q

This is placed below the table when the data written

are not original

A

Source Note :

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17
Q

The most commonly used method in presenting data by tabular method is
by constructing a X

A

Frequency Distribution Table.

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18
Q

is the organization of raw data in table

form, using classes and frequencies.

A

frequency distribution

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19
Q

Frequency Distribution Table (FDT) is a statistical table
showing the frequency or number of observations contained in
each of the defined X

A

classes or categories.

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20
Q

frequency distribution for qualitative data X all
categories and the number of elements that belong to
each of the categories

A

lists

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21
Q

The X of a category is obtained by dividing the
frequency(𝑓) for a category by the sum of all the frequencies(𝑛). They
are commonly expressed as percentages

A

relative frequency

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22
Q

frequency distribution for X, the data are grouped according to some numerical characteristics

A

quantitative

distributions

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23
Q

endpoints of a class interval

A

Class Limits –

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24
Q

represents the largest data value that can be

included in the class.

A

. Upper Class Limit -

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25
Q

represents the largest data value that can be

included in the class

A

Lower Class Limit -

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26
Q

used to separate the classes so that there are no
gaps in the frequency distribution. The gaps are due to the limits; for
example, there is a gap between 30 and 31.

A

Class boundaries -

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27
Q

lower boundary formula

A

Lower boundary = Lower Limit – 0.5

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28
Q

Upper boundary formula

A

Upper boundary = Upper limit + 0.5

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29
Q

the difference between the boundaries for any class., i.e.

i=upper boundary – lower boundary or i=(upper limit-lower limit) +1

A

. Class width (i)-

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30
Q

the midpoint of the class

A

Class mark -

31
Q 
total number of
observations less than the upper boundary of a class
interval
A

• less than cumulative frequency (

32
Q 
total number of
observations greater than the lower boundary of a class
interval
A

greater than cumulative frequency (>cf) –

33
Q

The purpose of X in

statistics is to convey the data to the viewers in pictorial form

A

graphs

34
Q

is a graph composed of bars whose heights are the

frequencies of the different categories.

A

A bar graph

35
Q

displays
graphically the same information concerning qualitative data that
a frequency distribution shows in tabular form.

A

bar graph

36
Q

is also used to graphically display qualitative

data.

A

pie chart

37
Q

a circle is divided into portions
that represent the relative frequencies or percentages
belonging to different categories.

A

pie chart

38
Q

the categories are placed along the
horizontal axis and frequencies are marked along the vertical
axis

A

bar graph

39
Q 
is a graph that displays the data by using
contiguous vertical bars (unless the frequency of a class is 0)
of various heights to represent the frequencies of
the classes.
A

histogram

40
Q

is a graph that displays the data by
using lines that connect points plotted for the frequencies at the
midpoints of the classes

A

frequency polygon

41
Q

The frequencies in a frequency polygon are represented by the

A

heights of the points

42
Q

is a graph that represents the cumulative

frequencies for the classes in a frequency distribution.

A

ogive

43
Q 
is a graph in which a point is plotted above each
class boundary at a height equal to the cumulative frequency
corresponding to that boundary.
A

ogive

44
Q

birth order

A

ordinal

45
Q

registration number

A

nominal

46
Q

skin complexion

A

nominal

47
Q

number of siblings

A

ratio

48
Q

gender

A

nominal

49
Q

every seventh customer entering a shopping mall is asked to select his or her favorite store

A

systematic

50
Q

nursing supervisors are selected using random numbers to determine annual salaries

A

simple random

51
Q

relative frequency counts the number of observations that are ordered less than the particular class

A

false

52
Q

the frequency of a category is defined as the number of observations in a data set falling under a category

A

true

53
Q

class limits and class boundaries are the same

A

true

54
Q

gathered data should be presented organized, precise, and convenient

A

false

55
Q

the endpoints of a class interval are called class boundaries

A

false (class limits)

56
Q

IQ score

A

interval*

57
Q

grade-level/year-level

A

?*

58
Q

blood sugar level

A

interval

59
Q

every 50th bottle of soda in a manufacturing line is checked to determine the amount of soda dispensed by the manufacturer

A

systematic

60
Q

in a large company, three departments are selected for a physical fitness test

A

clustered*

61
Q

it is important to keep the width of each class the same in a frequency distribution

A

true

62
Q

it is impossible to construct a frequency distribution for nominal data

A

true*

63
Q

in constructing a frequency distribution table, the classes must be mutually exclusive

A

true

64
Q

class limits are useful in tabulating continuous data

A

true

65
Q

Volume (in cu. cm)

A

I

66
Q

religious affiliation

A

N

67
Q

Blood Type

A

N

68
Q

Land area (in hectares)

A

R

69
Q

MAil carriers of a large city are divided into four groups according to gender and according to whether they walk or ride on their routes. Then 10 are selected from each group and interviewed to determine whether they have been bitten by a dog in the last year.

A

Stratified

70
Q

Nursing supervisors are selected using random numbers to determine annual salaries

A

simple random

71
Q

The frequency distribution table is the most used tabular presentation of data

A

true

72
Q

Frequency Distribution Table can be constructed for sets of Nominal data

A

true

73
Q

class limits are used in tabulating continuous data

A

true

Applied Statistics (6 decks)

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