chapter 5/week 5

Question 1

sample

Answer 1

a subset of a population

Question 2

sampling

Answer 2

the process by which a researcher selects a sample of participants for a study from the population of interest
- Many different ways

Representative sample

Question 3

Representative sample

Answer 3

one which we can draw accurate, unbiased estimates of the characteristics of the large population

Question 4

Sampling error

Answer 4

the extent to which characteristics of individuals selected for the sample differ from those of the population

Because of sampling error, results obtained from the sample differ from what would have been obtained using the whole population

Sampling error is important only if the sample is a probability sample

Question 5

Margin of Error (error of estimation)

Answer 5

indicates the degree to which the data obtained from the sample are expected to deviate from the population

Question 6

Factors that effect margin of error (error of estimation)

Answer 6

Sample size
Population size
Variance of the data

Question 7

A sample will be more similar to the population (i.e., smaller measurement error) when:

Answer 7

The sample size is large
The population size is smaller
The variance in the data is smaller

Question 8

Probability sample

Answer 8

a sample for which the researcher knows the probability that any individual in the population is included in the sample

Question 9

Probability sampling

Answer 9

a sample that is selected in such a way that the likelihood that any particular individual in the population will be selected for the sample can be specified

Question 10

(probability sample) obtained in four basic methods:

Answer 10

simple random sampling
Systematic sampling
Stratified random sampling
Cluster sampling

All cases in the population have an equal probability of being chosen for the sample

Question 11

sampling decision tree

Answer 11

do you have population level data? –> yes (probability sampling) or no (no probability sampling)

yes –> simple random sampling, systematic sampling, stratified random sampling, cluster sampling

no –> convenience sampling, quota sampling, purposive

If you know the population parameters the you conduct probability sampling

Question 12

simple random sampling

Answer 12

every possible member of the population has the same chance of being selected from the population
- When a sample is chosen in such a way that every possible sample of the desired size has the same chance of being selected from the population

Requires a sampling frame

Table of random numbers

Question 13

sampling frame

Answer 13

a list of the population from which the sample is to be drawn; difficult for big samples

Question 14

Table of random numbers

Answer 14

contains long rows of numbers that have been generated in a random order
- Typically use computers today

Question 15

systematic random sampling

Answer 15

every kth person is selected

Not all individuals in the population have equal chance

Question 16

Stratified Random Sampling

Answer 16

the population is divided into strata, then participants randomly selected from each stratum

Stratum

The strata should be exclusive (can’t have a person qualified for more than one group)

This method ensures that researchers have an adequate number of participants from each stratum

proportionate sampling method

Question 17

stratum

Answer 17

a subset of the population that shares a particular characteristic

Question 18

Proportionate sampling method

Answer 18

cases are sampled from each stratum in proportion to their prevalence in the population

Question 19

cluster sampling

Answer 19

sample groupings or clusters of participants

Clusters are based on naturally occurring groups that are usually in close proximity
Clusters of population, then randomly select clusters (not getting data from all clusters)

Question 20

Multistage Cluster Sampling

Answer 20

divide population into large clusters and randomly sample clusters; then randomly sample smaller clusters within those large clusters
- Then if needed, sample again from those clusters and continue until the appropriate number of participants is chosen

Question 21

Difficulties in Probability Sampling

Answer 21

nonresponse problem
misgeneralization

Question 22

nonresponse problem

Answer 22

failure to obtain responses from individuals that researchers select for their sample

Factors contributing:
- Personality characteristics
- Lack of time
- Literacy or language proficiency
- Sensitive topics
- Suspicion about the researcher/researcher/topic

Question 23

misgeneralization

Answer 23

generalizing results from a study to a population that differs in important ways from the one from which the sample was drawn

Ex: a researcher studying parental attitudes may study a random sample of parents who have children in the public school system; then uses his data to make generalizations about all parents – misgeneralization because parents whose children attend private or homeschooled are not included

Question 24

Nonprobability Sampling

Answer 24

researchers do not know the probability that a particular case will be chosen for the sample

• The error of estimation cannot be calculated
• Most research involves this type of sampling
• It is a valid method because the goal is to test hypotheses regarding how particular variables relate to behavior - not to describe how a particular population behaves

Question 25

types of non probability sampling

Answer 25

convenience quota purposive

Question 26

Convenience Sampling

Answer 26

use whatever participants are readily available Researchers often use convenience samples of college students. Because a college sample may differ from the population at large, some results may not generalize to all people Stopping people on the street, study patients at a local hospital, test students at a nearby school, our college Easy

Question 27

Quota Sampling

Answer 27

convenience sample in which the researcher takes steps to ensure that certain kinds of participants are obtained in particular proportions Ex - you may wish to obtain an equal number of children with ADHD and children without ADHD in your study ex - Wanting an equal proportion of male and female participants; sampling 60 women and 60 men

Question 28

Purposive Sampling (Deliberate Sampling)

Answer 28

researchers use their judgements to decide which participants to include in the sample, trying to choose respondents who are typical of the population Ex - pick a school district that represent the nation and work on that district alone to make predictions about the population - Similarly, pick a county that vote along the lines of national voting behavior in past elections and sample from there Based on previous elections, researchers have identified particular areas of the country that usually vote like the country as a whole; votes from these areas are interviewed and used to predict the outcome of an upcoming election

Question 29

economic sample

Answer 29

a sample that provides a reasonable degree of accuracy at a reasonable cost in terms of money, time, and effort

Question 30

Power

Answer 30

the ability of your design to find any effects of the variables being studied High power, better chance to detect the effect. Low power failure to detect an effect that exist in the data

Question 31

power's associations

Answer 31

1. Association between power and sample size - The larger the sample, the larger the power 2. Association between power and effect size - The larger the effect size, the larger the power To detect smaller effect sizes you will need more power (i.e., larger sample size)