Week 3- Sampling

Question 1

Standard deviation

Answer 1

A quantity expressing by how much the members of a group differ from the mean value of a group

Question 2

Normal distribution

Answer 2

Bell shaped
Most data is located near the mean
Parametric? 
Mean median and mode are approx same number 
68, 95, 99 rule applies

Question 3

Positive distribution

Answer 3

Small number of HIGH scores as outliers
Mean (average) is pulled away from 0
Mean follows meanies

Question 4

Negative distribution

Answer 4

Small number of LOW scores as outliers

Mean is pulled towards 0 (lower than the median)

Question 5

68%, 95%, 99% rule

Answer 5

+/- 1SD= 68%
+/- 2SD= 95%
+/- 3SD= 99%

Normal distribution

Question 6

Random sampling (probability sampling)

Answer 6

Where each person in the population has an equal chance of being selected

Reduces sampling bias

REQUIRES SAMPLING FRAME

Question 7

Sampling frame

Answer 7

Required in all forms of random sampling techniques

List of names

Question 8

Simple random

Answer 8

Random sampling technique

‘Names out of a hat’ each person has an equal chance of being selected

Con: has the potential to result in non-proportional results eg. Could result in 900 females and 50 males

Question 9

Systematic random

Answer 9

Random sampling technique

System to it, every X number person on the sampling frame

Pro: easy to administer

Con: prone to bias if there is already a system in the sampling frame eg. Every 4th person is male by chance

Question 10

Stratified random

Answer 10

Random sampling technique

Divide population into groups based on specific characteristics eg. Suburb they live in. Then a proportion is selected from each group and this becomes the sample.

Pro: decreases sampling error. More representative sample

Con: very logistic and resource heavy. Can be difficult to implement

Question 11

Cluster

Answer 11

Random sampling technique

Divide the population into groups eg. Perth suburbs. Then randomly select 2 or more groups then sample EVERYONE within the groups.

Pro: cost effective. Quick

Con: increased risk of sampling error

Question 12

Sampling error

Answer 12

An error caused when observing a sample, not the whole population

All studies have some sampling error as it’s impossible to sample everyone

Question 13

Non-random sampling

Answer 13

Easier to implement as there is no sampling frame

Prone to increased sampling bias

Question 14

Convenience

Answer 14

Non-random sampling technique

Easy. Whoever is conveniently available.

Pro: cost effective

Con: very bias sample, limits how far we can generalise our results

Question 15

Purposive

Answer 15

Non- random sampling type

Similar to convenience, going out and finding people who fill a specific criteria

Pro; cost effective.

Con: limits external validity

Question 16

Quota

Answer 16

Non-random sampling technique

Used by people selling in shopping centres etc. reach a predefined quota of a specific characteristic

Pro: cost effective. Researched has a bit more control over demographic differences

Con: not random- biased sample

Question 17

Snowball

Answer 17

Non-random sampling technique

First person recruits people who also fulfil the criteria

Pro: good for hard to reach populations eg. Sex workers

Con: can mean everyone is the same

Question 18

Type 1 error

Answer 18

FALSE POSITIVE

wrongly REJECTING null hypothesis when it’s actually true

Eg. The null hypothesis is true.
Meaning no association between two variables

Question 19

Type 2 error

Answer 19

FALSE NEGATIVE

wrongly accepted null hypothesis when the alternative hypothesis is correct

Eg. Null hypothesis should have been rejected
There IS a relationship between the two variables