Research Sampling

Question 1

In general ,what are the two types of sampling? Which is preferred?

Answer 1

nonprobability and probability

probability is preferred

Question 2

What are the negatives with nonprobability sampling?

Answer 2

there are problems with representativeness, so it’s less generalizable

lower confidence in findings

Question 3

What are the four common methods of nonprobablility sampling?

Answer 3

purposive

convenience

snowball

quota

Question 4

What does probability sampling avoid?

Answer 4

Sampling bias

Question 5

What is random selection?

Answer 5

all members have an equal chance of being selected

Equal Probability of Selection Method

Question 6

What theory allows us to estimate the accuracy and representativeness of a sample?

Answer 6

probability theory

Question 7

In sampling, what is an element?

Answer 7

an individual member of the population

Question 8

what do you call the list of all the elements in a population?

Answer 8

the sampling frame

Question 9

What is a parameter?

Answer 9

a summary of a given variable in a population - can be the population mean for example

Question 10

What is a statistic and how is it different from the parameter?

Answer 10

It is the summary of agiven variable in a SAMPLE, not the whole population

the goal is to get the statistic as close as possible to the true parameter

Question 11

What is the sampling idstribution?

Answer 11

the set of all the possible random samples that oculd be selected

Question 12

What are the 4 commonly used types of random sampling design?

Answer 12

simple random

systematic

stratified

multistage cluster

Question 13

Describe simple random sample

Answer 13

just straight random

get a sampling frame, assign numbers to eah, select by random number

Question 14

Describe systematic sampling

Answer 14

you figure out the n you want

divide the population total by the n, this is the sampling interval k

list and number into the sampling frame

then start with a random number and select every k-th element within the population

Question 15

What does it mean to avoid periodicity in systematic sampling?

Answer 15

you have to make sure the list isn’t oragnized in a specific way because you may miss out on a whole set if your random start number is far down

Question 16

Describe stratified samplin

Answer 16

you random sample from sub populations to ensure better representativeeness and decrease sampling error

So stratify the list, figure out what percentage there are in each group, then randomly sample that percentage from each group.

Question 17

What is oversampling?

Answer 17

It’s when you use stratified sampling and take more out of a group than their general percentage.

do this is the group you want to look at is really small percentage wise

Question 18

What is cluster sampling?

Answer 18

you cluster the gruop of elements first , randomly sample

then randomly sample them again

so randomly sample hospitals first, then randomly sample PAs from the selected hospitals

Question 19

What is the pro and con of cluster sampling?

Answer 19

it helps with cost and dispersed populations

it increases sampling error potential because you take two samples, so you double the error opportunity

Question 20

FOr experiments, what is a greater concern than representativeness?

Answer 20

comparability of the control of experimental groups

they need to be randomized in sch a way that the groups don’t differ in a systematic way

Question 21

what is sampling error?

Answer 21

variation in values ofyour sample mean compared to the population mean due to sampling

there will ALWAYS be some sampling error, the goal is to minimize

Question 22

What are the 2 ways you can reduce smapling error?

Answer 22

increase the n

increase homogeneity (decrease variance)

Question 23

In the normal curve, what percentage falls within 1 SD? 2SD? 3 SD?

Answer 23

68% between -1 and 1

95% between -2 and 2

99.7% between -3 and 3

Question 24

What normal distribution is called the z-distribution

Answer 24

when the mean is 0 and the SD is 1

Question 25

What is the critical z-score for a 90% co95%? 99%?nfidence interval?

Answer 25

1. 65 = 90% CL
2. 96 = 95% CL
3. 58 = 99% CL

Question 26

What is the confidence level? What is anothe rname for it? What do we usually set it as?

Answer 26

it’s the probability our sample statistic will fall within a confidence interval

it’ salso called alpha

usually set at -05, meaning we are 95% confident it will fal within a confidence interval

Question 27

What is a confidence interval?

Answer 27

It’s the range within which the true parameter should lie - it’s a range around the estimate with an upper and lowe rlimit

Question 28

If we want a confidence level of 95%, what is the equation for the confidence interval?

Answer 28

CI = mean +/- (1.96)(standard errors)

Question 29

If they give standard deviations, what do you need to calculate before finding the CI?

Answer 29

the standard errors

SE = SD/square root of the n

Question 30

What wideth of the confidence interval depends on which 3 things?

Answer 30

the alpha (confidence level)

the n - higher n, narrower interval

variation - higher variation more error wider interval