Reasearch Methods Section

Question 0

What is Spearmans RHO?

Answer 0

Spearmans Rho can be used in the following scenario: A study teasting for a relationship, using ordinal/interval data.

Question 1

What is mode?

Answer 1

Data Collection - Mode
Mode: Most common value.

Data: Type: Nominal.

Pros: Useful for categorised data.

Cons: Not useful if there are several common values in the data.

Mode is a measure of central tendency.

Question 2

What are Wilcoxon’s Test pairs?

Answer 2

Wilcoxon T can be used only in the following scenario: A study testing for a difference, using repeated measures or matched pairs with ordinal/interval data.

Question 3

What is the sign test?

Answer 3

Sign Test can be used only in the following scenario: A study testing for a difference, using repeated measures or matched pairs with nominal data.

Question 4

What is Mann Whitney U?

Answer 4

Mann Whitney U can be used only in the following scenario: A study testing for a difference, using independent groups with ordinal/interval data.

Question 5

What is Chi squared?s

Answer 5

Chi Square can be used in two scenarios. It is always used for nominalisation data. It can be used for either studies testing for a relationship or difference. If it is used in the case of testing for a difference then it must also be used when independent groups are.
To summarise: Independent Groups? Chi Square (if the following)
Nominal? Chi Square

Question 6

What is a Bar chart used for?

Answer 6

Bar Chart = Nominal/Ordinal data.

Question 7

What is a Histogram used for?

Answer 7

Histogram = Interval/Ratio data.

Question 8

What is a scatter graph used for?

Answer 8

Scattergraph = Correlational

Question 9

All about Range

Answer 9

Data Collection - Range
Range: The difference between the highest and lowest value.
Data Type: Ordinal.
Pros: It’s easy to calculate/provides direct information.
Cons: Affected by extreme values.
Range is a measure of dispersion.

Question 10

All about Standard Deviation

Answer 10

Data Collection - Standard Deviation
Standard Deviation: Displays the spread of data around the mean.
Data Type: Interval/Ratio.
Pros: All the data is taken into account which gives it precision.
Cons: It can hide parts of the data e.g. extreme values.
Standard deviation is a measure of dispersion.

Question 11

All about Mode

Answer 11

Data Collection - Mode
Mode: Most common value.
Data: Type: Nominal.
Pros: Useful for categorised data.
Cons: Not useful if there are several common values in the data.
Mode is a measure of central tendency.

Question 12

All about median

Answer 12

Data Collection - Median
Median: The centre value in an ordered list.
Data Type: Ordinal.
Pros: Is not affected by extreme parts of data.
Cons: Not as sensitive to values in the data (e.g. compared to the mean).
Median is a measure of central tendency.

Question 13

All about Mean

Answer 13

Data Collection - Mean
Mean: Add up all the numbers and then divide by the quantity of numbers.
Data Type: Interval/Ratio.
Pros: Uses all of the values in the data set.
Cons: It can misrepresent data if there are numbers extremely high or low.
Mean is a measure of central tendency.

Question 14

What is interval/ratio data?

Answer 14

Data that is separated by exact intervals. The difference between interval and ratio data is that interval data has no true zero point whereas ratio data does. E.g. measuring everyone’s height in cm to accurately know the differences between heights.

Question 15

What is ordinal data?

Answer 15

Data that is ranked by order. E.g. Lining people up by height where the difference between each person is not necessarily the same.

Question 16

What is nominal data?

Answer 16

Data that is categorised. E.g. putting people into groups according to height, “short, average, tall”.

Question 17

What are the pros and cons of Quota sampling?

Answer 17

Less time consuming than other sample methods (e.g. stratified sample).
May be biased due to it’s opportunity nature.

Question 18

What are the pros and cons of stratified sampling?

Answer 18

It’s more representative of the target population than other methods (e.g. volunteer sample).
It can be more time consuming to work out the strata than other methods (e.g. opportunity sample).

Question 19

What are the pros and cons of systematic sampling?

Answer 19

Less biased than other sampling methods (e.g. volunteer) as participants are selected using an objective method
Lists may not be available or easily constructed of the target population

Question 20

What are the pro and cons of random sampling?

Answer 20

Can be more representative than other methods (e.g. volunteer) as each member of the target population has equal chance of being selected
People chosen to take part not want to which could still lead to a biased sample

Question 21

What are the pros and cons of volunteer sampling?

Answer 21

Can avoid potential ethical issues e.g. lack of consent.
Biased because extraneous factors may influence why they chose to volunteer e.g. only the highly motivated/people with time available (Volunteer Bias

Question 22

What are the pros and cons of opportunity sampling?

Answer 22

More practical than other methods (e.g. quota sampling)

Creates a biased sample due to only using people available at a specific time, often in a specific location.

Question 23

What is quota sampling?

Answer 23

A stratified sample except not randomly selecting participants (usually volunteer or opportunity).
Still try to ensure important proportions of the target population however any number of the target population is acceptable.
E.g. if you are asked to be a part of their study then you are a member of their target population but if you’re not stopped then they’ve probably fulfilled their quota that you fit into or they don’t need you as a part of their target population.
Researcher: Whatup we need 21 males to every 20 females but Idc about their hair colours so let’s not ratio that.

Question 24

What is stratified sampling?

Answer 24

Subgroups within the population are noted (e.g. male/female)
Participants are obtained from the strata in ratio to the number of people in each subgroup (e.g. if there is a 2:1 ratio male/female then 2:1 ratio is used in sample)
The selection of p’s beyond the ratios is done randomly
Researcher: You were gathered here today because you perfectly fit our desired 2:1 male to female ratio for this club so walk around like “whatup”.

Question 25

What is systematic sampling?

Answer 25

Every xth (e.g. fourth or tenth) person is chosen to take part in the study from target sample
Researcher: I have gathered you here today for my study as you each entered the club like “whatup I’m the tenth visitor today!”.

Question 26

What is random sampling?

Answer 26

Every member of the target population has an equal chance of appearing in the sample.
Usually involves a random number generator or picking names from a hat
So it’s literally a raffle to take part in some dope-ass study.

Question 27

What is volunteer sampling?

Answer 27

People who volunteer to take part in the study
Usually done by placing an advert to request participants
So basically you write an ad like “whatup I pay peeps to be in my study” and they respond with “whatup yeah lemme get that sweet dolla”.

Question 28

What is opportunity sampling?

Answer 28

Participants who are readily available
They are likely to have been gathered for a different reason
So basically you walk into the club like “whatup I want you for my study”.

Question 29

What’s the issue with the experimental design of Independant Groups?

Answer 29

Order Effects (boredom, tiredness, practice).
Demand Characteristics (participants guessing the study’s purpose).

Question 30

What’s the experimental design issue with Repeated Measures?

Answer 30

Participant Effects (differences between individual participants).

Question 31

What’s the experimental design issue with matched pairs?

Answer 31

It’s difficult and time consuming to match participants

A large quantity of participants would be needed.

Question 32

What are Independent groups?

Answer 32

Independent Groups (IG) - Every participant experiences only one level or condition of the IV

Question 33

What are matched pairs?

Answer 33

Matched Pairs - IG - except participants in each group are matched e.g. for every male in Group 1 there is a male in Group 2 etc (how the participants are matched depends on what the researcher is looking for).

Question 34

What are repeated measures?

Answer 34

Repeated Measures - Every participant experiences every level or condition of the IV.

Question 35

What is the IV?

Answer 35

IV - Manipulated by the researcher

Eg. The temperature of the room.

Question 36

What is the DV?

Answer 36

DV - Measurable outcome of an experiment that is caused by the IV

Eg. Their test scores.

Question 37

What is an operationalised hypothesis?

Answer 37

An operationalised hypothesis is one where all the variables are in a form that can be easily measured.
DV - Explain the units of measurement
IV - Explain the different conditons/levels

Question 38

What is a directional hypothesis?

Answer 38

Directional - Temperature will decrease concentration.

Question 39

What is an nondirectional hypothesis?

Answer 39

Non Directional - Temperature will influence concentration.

Question 40

What is a null hypothesis?

Answer 40

Null hypothesis - Temperature will not affect concentration.