問題一覧
1
– is a branch of mathematics that deals with the collection, organization, presentation,
analysis, and interpretation of data.
Statistics
2
consist of methods for organizing, presenting, and describing data
by using tables, graphs, and summary measures.
Descriptive Statistics
3
is concerned with inferring or drawing conclusions about the
population based from pre-selected elements of that population.
Inferential Statistics
4
refer to the fundamental quantities that do not change in value
Constant
5
are quantities that may take anyone of a specified set of values.
Variables
6
are non-measurable characteristics that cannot be
assume a numerical value but can be classified into two or more categories.
Qualitative (Categorical) Variables
7
are those quantities that can be counted with your
bare hands, can be measured with the use of some measuring devices, or can be calculated
with the use of mathematical formula.
Quantitative (Numerical) Variables
8
are variables that are countable and can assume only a certain
values with no intermediate values.
Discrete Variables
9
are variables that can assume any value over a certain interval
or range, and we cannot count these variables.
Continuous Variables
10
are numbers or measurements that are collected as a result from observation, interview,
questionnaire, experimentations, test and so forth.
Data
11
is a set of data that have been processed and presented in a form suitable for human
interpretation
Information
12
is a first-hand information that is obtained usually by means of personal
interview and actual observation.
Primary Source
13
is taken from other’s works, news reports, and readings.
Secondary Source
14
applies to the data can be ranked and for which all arithmetic operation can
be done, it also takes into account the interval size and ratio of two related quantities,
which are usually based on a standard measurement
Ratio Scale
15
applies to data that can be ranked and for which we can find the
difference between two values can be calculated and interpreted
Interval Scale
16
applies to data that are divided into different categories that can be
ranked
Ordinal Scale
17
applies to data that are into different categories and these are used only
for identification purposes.
Nominal Scale
18
– is a person-to-person interaction between an interviewer
and an interviewee.
Direct or Interview Method
19
– is an alternative method for the interview method.
Written responses are obtained by distributing questionnaires to the respondents through
mail or hand-carry
Indirect or Questionnaire Method
20
– is enforced by private organizations or government agencies for
recording purposes
Registration Method
21
– is a scientific method of investigation that makes possible use of
all senses to measure or obtain outcomes/responses from the object of study.
Observation Method
22
– is used when the objective is to determine the cause and effect of a
certain phenomenon under some controlled conditions.
Experimentation
23
consists of all elements – individuals, items, or objects – whose characteristics are
being studied
Population
24
is a portion of the population selected for study.
Sample
25
is any numerical value describing a characteristic of population.
Parameters
26
in determining the Sample Size
The sample size can be obtained by the formula
Slovin’s Formula
27
is a vital tool if the information gathered would be
used for administrative purposes and if it is local or national concern.
Complete Enumeration or Census Taking
28
is the most commonly used sampling technique in which each member in
the population is the given as equal chance of being selected in the sample.
Random Sampling
29
is a method of collecting a small portion of the population by which not
all the members is the population are given the chance to be included in the sample
Non-random Sampling
30
– means that each member of the population has an equal chance of
being selected and included in the sample.
Equiprobability
31
– means that the chance of one member being drawn does not affect the
chance of the other member
Independence
32
– involves certain restrictions intended to improve the
validity of the sampling. This design is applicable only when the population being
investigated requires homogeneity.
Restricted Random Sampling
33
is considered the best random sampling design
because there were no restrictions imposed and every member in the population has an
equal chance of being included in the sample.
Unrestricted Random Sampling
34
This is done by simply writing the names or numbers
of all the members of the population in the small rolled pieces of paper which are later
placed in a container.
Lottery or Fishbowl Sampling
35
– this method of sampling is done by taking every kth element in
the population. It applies to a group of individuals arranged in a waiting line or in a
methodical manner.
Systematic Sampling
36
– when the population can be partitioned into several
strata or subgroups, it may be wiser to employ the stratified technique to ensure a
representative of each group in the sample
Stratified Random Sampling
37
– when the population is grouped into more
or less homogeneous classes, that is, different groups but with a relatively common
characteristic, then can be sampled independently by taking equal number of
elements from each stratum.
Simple Stratified Random Sampling
38
– In some cases, the characteristics of
the population is such that the proportions of the subgroups are grossly equal. The Stratified Proportional Random Sampling – In some cases, the characteristics of
the population is such that the proportions of the subgroups are grossly equal. The
Stratified Proportional Random Sampling
39
– This method is an extension or a multiple
application of the stratified random sampling technique. The number of stages depends
on the number of population and the sample size needed in the survey
Multi-stage or Multiple Sampling
40
– Also referred as non-random or non-probability
sampling. It plays a major role in the selection of a particular item or in making decisions in the
cases of incomplete responses or observation. This is usually based on a certain criteria laid
down by the researcher or his adviser.
Judgement or Purposive Sampling
41
– This is a relatively quick and inexpensive method to operate since the
choice of the number of persons or elements to be included in a sample is done at the
researcher’s own convenience or preference and is not predetermined by some carefully operated
randomizing plan.
Quota Sampling
42
– referred to as an area sampling because it is usually applied on a
geographical basis. The population is group into cluster or small units, e.g., blocks or districts, in
city or municipality.
Cluster Sampling
43
– this design is applied to those samples which are taken because they
are most available.
Incidental Sampling
44
– this method has been widely used in television and radio programs to
find out opinions of TV viewers and listeners regarding a controversial issue.
Convenience Sample
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22問 • 2ヶ月前問題一覧
1
– is a branch of mathematics that deals with the collection, organization, presentation,
analysis, and interpretation of data.
Statistics
2
consist of methods for organizing, presenting, and describing data
by using tables, graphs, and summary measures.
Descriptive Statistics
3
is concerned with inferring or drawing conclusions about the
population based from pre-selected elements of that population.
Inferential Statistics
4
refer to the fundamental quantities that do not change in value
Constant
5
are quantities that may take anyone of a specified set of values.
Variables
6
are non-measurable characteristics that cannot be
assume a numerical value but can be classified into two or more categories.
Qualitative (Categorical) Variables
7
are those quantities that can be counted with your
bare hands, can be measured with the use of some measuring devices, or can be calculated
with the use of mathematical formula.
Quantitative (Numerical) Variables
8
are variables that are countable and can assume only a certain
values with no intermediate values.
Discrete Variables
9
are variables that can assume any value over a certain interval
or range, and we cannot count these variables.
Continuous Variables
10
are numbers or measurements that are collected as a result from observation, interview,
questionnaire, experimentations, test and so forth.
Data
11
is a set of data that have been processed and presented in a form suitable for human
interpretation
Information
12
is a first-hand information that is obtained usually by means of personal
interview and actual observation.
Primary Source
13
is taken from other’s works, news reports, and readings.
Secondary Source
14
applies to the data can be ranked and for which all arithmetic operation can
be done, it also takes into account the interval size and ratio of two related quantities,
which are usually based on a standard measurement
Ratio Scale
15
applies to data that can be ranked and for which we can find the
difference between two values can be calculated and interpreted
Interval Scale
16
applies to data that are divided into different categories that can be
ranked
Ordinal Scale
17
applies to data that are into different categories and these are used only
for identification purposes.
Nominal Scale
18
– is a person-to-person interaction between an interviewer
and an interviewee.
Direct or Interview Method
19
– is an alternative method for the interview method.
Written responses are obtained by distributing questionnaires to the respondents through
mail or hand-carry
Indirect or Questionnaire Method
20
– is enforced by private organizations or government agencies for
recording purposes
Registration Method
21
– is a scientific method of investigation that makes possible use of
all senses to measure or obtain outcomes/responses from the object of study.
Observation Method
22
– is used when the objective is to determine the cause and effect of a
certain phenomenon under some controlled conditions.
Experimentation
23
consists of all elements – individuals, items, or objects – whose characteristics are
being studied
Population
24
is a portion of the population selected for study.
Sample
25
is any numerical value describing a characteristic of population.
Parameters
26
in determining the Sample Size
The sample size can be obtained by the formula
Slovin’s Formula
27
is a vital tool if the information gathered would be
used for administrative purposes and if it is local or national concern.
Complete Enumeration or Census Taking
28
is the most commonly used sampling technique in which each member in
the population is the given as equal chance of being selected in the sample.
Random Sampling
29
is a method of collecting a small portion of the population by which not
all the members is the population are given the chance to be included in the sample
Non-random Sampling
30
– means that each member of the population has an equal chance of
being selected and included in the sample.
Equiprobability
31
– means that the chance of one member being drawn does not affect the
chance of the other member
Independence
32
– involves certain restrictions intended to improve the
validity of the sampling. This design is applicable only when the population being
investigated requires homogeneity.
Restricted Random Sampling
33
is considered the best random sampling design
because there were no restrictions imposed and every member in the population has an
equal chance of being included in the sample.
Unrestricted Random Sampling
34
This is done by simply writing the names or numbers
of all the members of the population in the small rolled pieces of paper which are later
placed in a container.
Lottery or Fishbowl Sampling
35
– this method of sampling is done by taking every kth element in
the population. It applies to a group of individuals arranged in a waiting line or in a
methodical manner.
Systematic Sampling
36
– when the population can be partitioned into several
strata or subgroups, it may be wiser to employ the stratified technique to ensure a
representative of each group in the sample
Stratified Random Sampling
37
– when the population is grouped into more
or less homogeneous classes, that is, different groups but with a relatively common
characteristic, then can be sampled independently by taking equal number of
elements from each stratum.
Simple Stratified Random Sampling
38
– In some cases, the characteristics of
the population is such that the proportions of the subgroups are grossly equal. The Stratified Proportional Random Sampling – In some cases, the characteristics of
the population is such that the proportions of the subgroups are grossly equal. The
Stratified Proportional Random Sampling
39
– This method is an extension or a multiple
application of the stratified random sampling technique. The number of stages depends
on the number of population and the sample size needed in the survey
Multi-stage or Multiple Sampling
40
– Also referred as non-random or non-probability
sampling. It plays a major role in the selection of a particular item or in making decisions in the
cases of incomplete responses or observation. This is usually based on a certain criteria laid
down by the researcher or his adviser.
Judgement or Purposive Sampling
41
– This is a relatively quick and inexpensive method to operate since the
choice of the number of persons or elements to be included in a sample is done at the
researcher’s own convenience or preference and is not predetermined by some carefully operated
randomizing plan.
Quota Sampling
42
– referred to as an area sampling because it is usually applied on a
geographical basis. The population is group into cluster or small units, e.g., blocks or districts, in
city or municipality.
Cluster Sampling
43
– this design is applied to those samples which are taken because they
are most available.
Incidental Sampling
44
– this method has been widely used in television and radio programs to
find out opinions of TV viewers and listeners regarding a controversial issue.
Convenience Sample