Research Methods

Question 1

Define Replication Method.

Answer 1

Repeating your experiment to make it reliable.

Question 2

Define Confound.

Answer 2

Uncontrolled Independent Variable.

Question 3

Define Independent Variable and which axis it is usually measured on.

Answer 3

Variable that is manipulated by us to see if affects the dependent variable. This is measured on the X axis.

Question 4

Define Dependent Variable.

Answer 4

Measure of the behaviour we are interested in, it is affected by the independent variable. This is measured on the Y axis.

Question 5

Define what makes an experiment reliable in a psychology context. Provide an example.

Answer 5

If you can repeat the experiment over and over and get the same response then you have reliable results.

For a study to be reliable the same experiment must be conducted under the same conditions to generate the same results.

Question 6

Describe what makes your data valid in an experiment and provide an example.

Answer 6

Your data is valid if it answers what you wanted to know.

Question 7

Define Population in a research context.

Answer 7

All info/behaviours that we are interested in e.g. height, weight, score.

Question 8

Define what a sample is.

Answer 8

A representative group of your population.

Question 9

Describe 2 ways sampling can go wrong.

Answer 9

1. Sampling Bias

2. Sampling Error

Question 10

Define sampling bias with an example.

Answer 10

Sampling Bias is when your sample is systematic.

For example, if I wanted to know the strength of all the people in my lecture but only chose men, this would be sampling bias.

For Example, if I want to know whether Blue or Pink is more liked by children I need to have a mix of of ages, races, sexes in order to avoid sampling bias.

Question 11

Does Sampling Bias effect the validity or reliability? and why?

Answer 11

Sampling Bias effects the validity because you are not getting the true answer to your question.

Question 12

Define Sampling Error.

Answer 12

Sampling Error is when random samples are drawn from the same population and give different results. Happens by chance and is unavoidable but can be minimised by using large sample groups.

Question 13

3 things to ask when looking at a graph.

Answer 13

1. What are you measuring? (y axis)
2. How are you measuring it? (x axis)
3. What is the shape of the results?

Question 14

Describe Observational Design.

Answer 14

Observational Design is when we are observing and looking for a correlation between 2 dependent variables. There is no independent variables.

Question 15

List some critiques of Observational Design.

Answer 15

1. You cannot conclude anything because it has not been manipulated.
2. It is often the only choice for ethical and practical reasons.
3. Does not require sampling so it is more sound.

Question 16

Correlation does not imply causation, explain this.

Answer 16

Just because you see a correlation or link between 2 things does not mean they are the reason or cause of one another.

Question 17

Explain the basic principles of Experimental design.

Answer 17

1. You manipulate the Independent Variable to see if the effect on the dependent variable.
2. This can show or imply causation.
3. It is the more powerful design because you can identify causation.
4. It is not always the ethical or practical option but where possible we should use it.

Question 18

Name the 3 types of experimental design.

Answer 18

1. Within Subject Design
2. Between Groups Design
3. Matched Pairs Design

Question 19

Explain Within Subject Design. Provide an example.

Answer 19

This is when the subjects is exposed to all experimental condition of the independent variable. For example if I want to test the meteor of someone on the memory enhancing drug i would have subjects take the real pill and then at a different session take the placebo pill.

Question 20

List Critiques of Within Subject Design.

Answer 20

1. It is good for controlling some confounds because the subject is exposed to all options. E.g. They may have better memory naturally.
2. There is a strong possibility of external confounds as there is time between each session. E.g. sleep.
3. There can be a Risk of Order Effect. This is when you would have everyone take the same pill at the same time. You can remove the external confound but breaking it up and having some take it and one point while other take the second pill.

Question 21

Explain Between Groups Design

Answer 21

This is when each subject only participates in 1 level of the experiment and then we compare the groups.

Question 22

List Critiques of the Between Groups Design

Answer 22

1. This is good for controlling external confounds because there is no time difference and less change.
2. Possibility of subject confounds because you are using a different group of people for each level however you can minimise this by using random allocating.

Question 23

Explain Matched Pairs Design

Answer 23

This is when you give some sort of pretest before the experiment then match subjects up according to their results. You then assign them to alternate groups.

Question 24

List Critiques of the Matches Pairs Design.

Answer 24

1. This keeps the external confounds constant and nearly keeps the subject confounds constant too.
2. Labour intensive.

Question 25

Explain what Subject Blind is and it’s benefits.

Answer 25

This is when the subject doesn’t know which group they are. This can remove subject confounds or stop them from changing their behaviour.

Question 26

Explain Double Blind.

Answer 26

This is when the experimenter does not know which group is the control group and which group is the experiment group. This removes experimenter expectation.

Question 27

What should you do when looking at any research?

Answer 27

Ask if causation has been proved.

Question 28

Explain what a confound is.

Answer 28

These are the variables that could cause change for our DV, We want to remove these where possible to ensure we have reliable and valid data.

Question 29

Name 2 ways of eliminating confounds.

Answer 29

1. Holding the Confound Constant (standardisation)

2. Randomize the Confound (randomising)

Question 30

Explain what standardisation is.

Answer 30

This is when you make sure the confounds stay the same every time a subject participates. And it is the same for al subjects. Especially good for external confound e.g. environment.

Question 31

Explain Randomizing.

Answer 31

This is when you randomise the distribution of confounds between the subjects. It is especially good for internal confounds