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Y3 T2 Politics 256 > Text Ch.8 > Flashcards

Text Ch.8 Flashcards

1
Q

Sampling links in with ______ validity

A

external

-the extent to which the findings drawn from the cases under examination may be used to make generalizations about phenomena outside the original study. Concerned with representativeness.

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2
Q

Sampling Error is the difference between ______ _______ and ______ ______

A

Population Parameter and Sample Statistic

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3
Q

Population Parameter Vs Sample Statistic

A

p. p= population characteristics, expressed in numeric terms when the responses of each member (or case) of the population are measured
s. s=

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4
Q

Population Parameter Vs Sample Statistic

A

p. p= population characteristics, expressed in numeric terms when the responses of each member (or case) of the population are measured
s. s=a subset of the p.p

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5
Q

3 factors in sample representativeness

A
  1. Sample Frame
    -a list of the items or people forming a population from which a sample is taken.
    Consider:
    – Availability (or lack thereof)
    – Completeness
    – Accuracy
  2. Sample Selection
    - probability sampling
    - non probability sampling
  3. Sample size(if a probability sample)
    - as sample size goes up, error goes down
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6
Q

Describe differences between probability and non probability sampling

A

Probability Sampling

  • Based on probability theory
  • Can estimate likelihood of representativeness
  • Can estimate accuracy of sample statistics
  • Appropriate for statistical analysis
    types: • Simple random • Systematic selection • Stratified • Cluster

Non-Probability Sampling
-NOT based on probability theory
-CanNOTestimate likelihood of representativeness
-CanNOTestimate accuracy of sample statistics
-NOT appropriate for statistical analysis (including percentages/frequencies)
Types: Accidental and Purposeful(most typical)

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7
Q

Critiques of Sampling Frames: for probability sample and for Non-probability

A

Probability sample:

  • What are possible gaps in the list?
  • How could the sampling frame possibly introduce bias?

Non-probability sample:

  • Convenience or purposive sample?
  • Potential for ‘closed loops’?

.Does the goal of the research match the fact that it is non-probability or probability

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8
Q

Qualitative Research and NonprobabilitySampling

A

Words/text, rather than numbers
Deep description
Seeks transferable, dependable findings
Does not argue representativeness

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9
Q

Why use Non Probaility sampling

A

• Exploratory research
• Extremely small populations
• Unavailable/inadequate sampling frames
• High refusal populations
**Typically will stress that results may not be representative

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10
Q

Critiquing Sampling Size

A 
Probability sample: 
. Homogeneity of population 
. Number of variables 
. Sample selection
- Cluster sampling needs large sample sizes
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11
Q

Data Saturation

A

Data saturation: point at which data collection no longer provides the researcher with new information

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12
Q

Non Probability sampling: how to choose sampling size

A

Focus on quality of information obtained, rather than quantity of cases

Data saturation: point at which data collection no longer provides the researcher with new information

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13
Q

population

A

in research the group that a researcher wishes to generalize about(ex: Canadian citizens); in content analysis, the texts most appropriate for answering the research questions

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14
Q

sampling

A

the process of drawing a sample of cases from a larger population

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15
Q

First step in a research project is to clearly identify the population being studied: 3 factors

A
  1. Unit of analysis(indv,political parties,etc)
  2. Geographic location
  3. Reference perios
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16
Q

representative sample

A

one that accurately represents the larger population from which it was taken

17
Q

sampling frame

A

is a list of all of the units in the target population

18
Q

sample selection method

2 main categories

A
  1. probability

2. nON PROBABILITY

19
Q

Probability sampling

A

sampling based on probability theory allows us to estimate the likelihood that our sample provides a representative picture of the population
-random selection of a sample, each case in a population has an equal opportunity to be selected

20
Q

simple random sampling

A

the process by which every case in the population is listed and the sample is selected randomly from this list

21
Q

sampling distribution

A

theoretical distribution of a sample statistic (ex:the mean) for a given sample size

22
Q

confidence interval

A

the range of values within which the population parameter is likely to fall

23
Q

Sample Size

A

.when probability sampling techniques are used, sampling error is reduced as the sample size increases

24
Q

Homogeneity vs. Heterogeneity

A

refers to how similar a population is with respect to salient variables

refers to how dissimilar a population is

the more homogenous a population, the smaller the sample size needed

25
Q

3 factors that influence sample size needs

A
  1. Homogeneity of a population
  2. Desired Degree of accuracy
  3. The complexity(number of variables) of the research
26
Q

systematic selection

A

a probability sampling technique in which the researcher calculates a selection interval and uses it to select cases from the sampling frame

ex: is selection interval is 20, you select a number from 1-20 and start going 6, 26,46,66,86,106
- less random and less accurate than random sampling

27
Q

Stratified Sampling

A

.involves breaking the population into mutually exclusive subgroups, or strata, and then randomly sampling each group

  • each group is its own sampling frame
  • disproportionate stratified sampling is done when one subgroup of the population is way smaller but needs to be enhanced for sampling
  • Disproportionate is NOT representative of the population as a whole
28
Q

cluster sampling

A

is the process of dividing the population into a number of subgroups, known as clusters, and then randomly selecting clusters within which to randomly sample

  • saves time and money
  • not really representative either
29
Q

Types of probability sampling(3)

A
  1. Systematic selection
  2. stratifies sampling
  3. Cluster Sampling
30
Q

Types of non-probability sampling(2)

A
  1. accidental sampling
    - convenience or haphazard
    - the researcher gathers data from indv whome he or she accidently encounters or are convenient
    - self selection is just as biased
  2. Purposive(judgemental) sampling
    - involves researcher selection of specific cases; the researcher uses his or her judgement to select cases that will provide the greatest amount of info
    - snowball sampling is often employed to study social networks
    - quota sampling when accidentall or purposive sampling is combined with stratification
31
Q

T OR F

Non Probability sampling methods employ random selection of cases

A

FALSEEEEE
-this means that we cannot identify margins of error or confidence intervals; thus it is more difficult to make generalizations and draw conclusions about the general population

32
Q

When are non-probability sampling appropriate?

A

when researchers are not seeking to make generalizations about a larger population, but are pursuing more in-depth descriptive information
-also good for when probability sampling is not feasible: when sampling frames are inadequate, members of the population are likely to refuse to participate, or the population of study is extremely small

33
Q

Snowball sampling is what type of sampling?

describe Snowball sampling

A

non probability, purposive sampling

the researcher begins by identifying a few cases and , from these, gets referalls for other cases and continues to branch out

34
Q

spurious

A

the relationship between the independent and dependent variables that, while initially thought to be causal, is non-causal and is a function of the presence of athird variable, which causes the variation in both variables

35
Q

quota sampling is what type of sampling?

describe quota sampling

A

non probability and probability, purposive and stratified sampling

the researcher combines purposive or accidental sampling with stratification; the researcher identifies a number of target groups(strta) and then sets a quota number that must be met for each group

Y3 T2 Politics 256 (17 decks)

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