Chapter 9

Question 1

Opportunity samples

Answer 1

Most used by psychology students – sample of people who are available at that time

Question 2

population

Answer 2

the larger pool of who or what is to be tested

Question 3

sample

Answer 3

a portion or segment that is typical of the population – a good representation

Question 4

sampling plan

Answer 4

accurate sampling frame that defines the target population and then relying on a carefully designed blueprint

Question 5

probability sampling

Answer 5

randomness enters into the selection process at some stage so that the laws of mathematical probability apply

Question 6

probability

Answer 6

refers to the mathematical chance of event occurring

Question 7

unbiased

Answer 7

values produced by the sample must (on average) coincide with the true values of the population

Question 8

stability

Answer 8

there is not much variability in the sample values

Question 9

bias (systematic error)

Answer 9

the spread (or variability) among the sampling units indicates the instability

the distance between the true population value and the midpoint of the values of output units indicates bias

Question 10

simple random sampling

Answer 10

“simple” - the sample is selected from and undivided population
“random”- the sample is meant to be chosen by a process that will give every unit in the specific population the same chance of being chosen

Question 11

sampling with replacement

Answer 11

selected units are placed back into the sampling pool and can be repacked for subsequent draws

Question 12

sampling without replacement

Answer 12

a previously selected unit cannot be put back into the sampling pool to be repacked

Question 13

stratified random sampling

Answer 13

Efficient method of probability sampling

A separate sample is randomly selected from each homogenous stratum “layer” of the population.
Stratum means are weighted to form a combined estimate of the population

Question 14

area probability sampling

Answer 14

applicable to any population which can be divided into meaningful geographic area

Question 15

quota sampling

Answer 15

assigned a quota of people to be questioned and let the questioner build up a sample that was roughly representative of the population

Question 16

push polls

Answer 16

using rumours, half truths, lies etc. to push opinions in a particular direction rather than scientifically sample them

Question 17

margin of error

Answer 17

an amount which is allowed for miscalculation

Question 18

point estimates

Answer 18

tells us about some typical characteristics of the target population

Question 19

Interval estimates

Answer 19

tell us how much the point estimates are likely to be in error ( ex: because of variability in the composition of the population)

Question 20

confidence interval

Answer 20

indicates the probability that the estimated population value is correct within plus-or-minus some specified interval

Question 21

unbiased sampling

Answer 21

error of estimate gives us the bias of groupings and when we calculate an average if the error equal out to 0.00 we can say that the sample unbiased
- everyone has a chance of being chosen

Question 22

error of estimate

Answer 22

closeness of the point estimate compared to the true population value
- negative estimate is considered an underestimate and a positive estimate is considered an overestimate

Question 23

nonresponse bias

Answer 23

systematic error due to non participation
- ex: in phone interviews a lot of people tend to hang up either because they don’t have the time or they don’t want their privacy invaded

Question 24

effective sample size

Answer 24

size of the actual final sample

Question 25

volunteer bias

Answer 25

used to refer to systematic error resulting when the responses of people who volunteer differ from those in the general population

Question 26

representative

Answer 26

when a sample size is "typical" of the population