問題一覧
1
refers to numerical information
statistics
2
methods of organizing, summarizing, and presenting data in an informative way.
Descriptive Statistics
3
s A decision, estimate, prediction, or generalization about a population based o on a sample.
Inferential Statistics
4
. A population or sample may consist of _____ or ____
individuals or objects
5
is a collection of all possible individuals, objects, or measurements of interest.
population
6
is a portion, or part, of the population of interest
sample
7
- the characteristic being studied is nonnumeric.
Qualitative or Attribute variable
8
- information is reported numerically.
Quantitative variable
9
. can only assume certain values and there are usually "gaps" between values.
Discrete variables
10
can assume any value within a specified range.
Continuous variable
11
- data that is classified into categories and cannot be arranged in any particular order.
Nominal level
12
- with the additional property that meaningful amounts of differences between data values can be determined. There is no natural zero point.
Interval level
13
-data arranged in some order, but the differences between data values cannot be determined or are meaningless.
Ordinal level
14
-the interval level with an inherent zero starting point. Differences and ratios are meaningful for this level of measurement.
Ratio level
15
Properties:
1. Observations of a qualitative variable can only be classified and counted.
2. There is no particular order to the labels.
NOMINAL LEVEL DATA
16
Properties:
1. Data classifications are represented by sets of labels or names (high, medium, low) that have relative values.
2. Because of the relative values, the data classified can be ranked or ordered.
ORDINAL LEVEL DATA
17
Properties:
1. Data classifications are ordered according to the amount of the characteristic they possess.
2. Equal differences in the characteristic are represented by equal differences in the measurements.
INTERVAL LEVEL DATA
18
Properties:
1. Data classifications are ordered according to the amount of the characteristics they possess.
2. Equal differences in the characteristic are represented by equal differences in the numbers assigned to the classifications.
3. The zero point is the absence of the characteristic and the ratio between two numbers is meaningful.
RATIO LEVEL DATA
19
_____ is the "highest" level of measurement.
Ratio level
20
means that every member of the population has a chance of being selected. It is mainly used in quantitative research. If you want to produce results that are representative of the whole population, probability sampling techniques are the most valid choice.
Probability sampling
21
It is mainly used in quantitative research.
Probability sampling
22
. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals
Systematic sampling
23
- involves dividing the population into subpopulations that may differ in important ways.
3. Stratified sampling
24
To use this sampling method, you divide the population into subgroups (called strata) based on the relevant characteristic (e.g., gender identity, age range, income bracket, job role).
3. Stratified sampling
25
If it is practically possible, you might include every individual from each sampled cluster. If the clusters themselves are large, you can also sample individuals from within each cluster using one of the techniques above.
This is called multistage sampling
26
- also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.
Cluster sampling
27
, individuals are selected based on non-random criteria, and not every individual has a chance of being included.
Non-probability sampling methods
28
Non-probability sampling techniques are often used in _______ and _____. In these types of research, the aim is not to test a hypothesis about a broad population, but to develop an initial understanding of a small or under- 24searched population.
exploratory & qualitative research
29
simply includes the individuals who happen to be most accessible to the researcher.
Convenience sampling
30
1. Convenience sampling
A convenience sample simply includes the individuals who happen to be most accessible to the researcher.
This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can't produce generalizable results. Convenience samples are at risk for both _____
sampling bias and selection bias.
31
is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves (e.g. by responding to a public online survey).
2. Voluntary response sampling
32
This type of sampling, also known as judgement sampling, involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.
3. Purposive sampling
33
It is often used in qualitative research, where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences, or where the population is very small and specific.
3. Purposive sampling
34
. The number of people you have access to "snowballs” as you get in contact with more people. The downside here is also representativeness, as you have no way of knowing how representative your sample is due to the reliance on participants recruiting others. This can lead to sampling bias.
, snowball sampling
35
relies on the non-random selection of a predetermined number or proportion of units.
5. Quota sampling
36
These units share specific characteristics, determined by you prior to forming your strata.
5. Quota sampling
37
This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can't produce generalizable results
convenience sampling
38
Practically all quantitative data is recorded on the ratio level of measurement.
ratio level
39
is similar to simple random sampling, but it is usually slightly easier to conduct
systematic sampling
40
can be used to recruit participants via other participants
snowball sampling
41
It allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample.
stratified sampling
42
involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.
purposive sampling
2.1
2.1
Shekinah Bismonte · 58問 · 2年前2.1
2.1
58問 • 2年前2.1 (interactive multimedia)
2.1 (interactive multimedia)
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2.1 (interactive multimedia)
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LESSON 3.2
15問 • 1年前問題一覧
1
refers to numerical information
statistics
2
methods of organizing, summarizing, and presenting data in an informative way.
Descriptive Statistics
3
s A decision, estimate, prediction, or generalization about a population based o on a sample.
Inferential Statistics
4
. A population or sample may consist of _____ or ____
individuals or objects
5
is a collection of all possible individuals, objects, or measurements of interest.
population
6
is a portion, or part, of the population of interest
sample
7
- the characteristic being studied is nonnumeric.
Qualitative or Attribute variable
8
- information is reported numerically.
Quantitative variable
9
. can only assume certain values and there are usually "gaps" between values.
Discrete variables
10
can assume any value within a specified range.
Continuous variable
11
- data that is classified into categories and cannot be arranged in any particular order.
Nominal level
12
- with the additional property that meaningful amounts of differences between data values can be determined. There is no natural zero point.
Interval level
13
-data arranged in some order, but the differences between data values cannot be determined or are meaningless.
Ordinal level
14
-the interval level with an inherent zero starting point. Differences and ratios are meaningful for this level of measurement.
Ratio level
15
Properties:
1. Observations of a qualitative variable can only be classified and counted.
2. There is no particular order to the labels.
NOMINAL LEVEL DATA
16
Properties:
1. Data classifications are represented by sets of labels or names (high, medium, low) that have relative values.
2. Because of the relative values, the data classified can be ranked or ordered.
ORDINAL LEVEL DATA
17
Properties:
1. Data classifications are ordered according to the amount of the characteristic they possess.
2. Equal differences in the characteristic are represented by equal differences in the measurements.
INTERVAL LEVEL DATA
18
Properties:
1. Data classifications are ordered according to the amount of the characteristics they possess.
2. Equal differences in the characteristic are represented by equal differences in the numbers assigned to the classifications.
3. The zero point is the absence of the characteristic and the ratio between two numbers is meaningful.
RATIO LEVEL DATA
19
_____ is the "highest" level of measurement.
Ratio level
20
means that every member of the population has a chance of being selected. It is mainly used in quantitative research. If you want to produce results that are representative of the whole population, probability sampling techniques are the most valid choice.
Probability sampling
21
It is mainly used in quantitative research.
Probability sampling
22
. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals
Systematic sampling
23
- involves dividing the population into subpopulations that may differ in important ways.
3. Stratified sampling
24
To use this sampling method, you divide the population into subgroups (called strata) based on the relevant characteristic (e.g., gender identity, age range, income bracket, job role).
3. Stratified sampling
25
If it is practically possible, you might include every individual from each sampled cluster. If the clusters themselves are large, you can also sample individuals from within each cluster using one of the techniques above.
This is called multistage sampling
26
- also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.
Cluster sampling
27
, individuals are selected based on non-random criteria, and not every individual has a chance of being included.
Non-probability sampling methods
28
Non-probability sampling techniques are often used in _______ and _____. In these types of research, the aim is not to test a hypothesis about a broad population, but to develop an initial understanding of a small or under- 24searched population.
exploratory & qualitative research
29
simply includes the individuals who happen to be most accessible to the researcher.
Convenience sampling
30
1. Convenience sampling
A convenience sample simply includes the individuals who happen to be most accessible to the researcher.
This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can't produce generalizable results. Convenience samples are at risk for both _____
sampling bias and selection bias.
31
is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves (e.g. by responding to a public online survey).
2. Voluntary response sampling
32
This type of sampling, also known as judgement sampling, involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.
3. Purposive sampling
33
It is often used in qualitative research, where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences, or where the population is very small and specific.
3. Purposive sampling
34
. The number of people you have access to "snowballs” as you get in contact with more people. The downside here is also representativeness, as you have no way of knowing how representative your sample is due to the reliance on participants recruiting others. This can lead to sampling bias.
, snowball sampling
35
relies on the non-random selection of a predetermined number or proportion of units.
5. Quota sampling
36
These units share specific characteristics, determined by you prior to forming your strata.
5. Quota sampling
37
This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can't produce generalizable results
convenience sampling
38
Practically all quantitative data is recorded on the ratio level of measurement.
ratio level
39
is similar to simple random sampling, but it is usually slightly easier to conduct
systematic sampling
40
can be used to recruit participants via other participants
snowball sampling
41
It allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample.
stratified sampling
42
involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.
purposive sampling