Research Methods Flashcards

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1
Q

What is a hypothesis?

A

A precise testable statement that states the relationship between the IV and DV. (You can also think of it as a prediction). e.g. People with an audience will throw more balls into a bucket from 2m away than people without an audience.

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2
Q

What is the difference between the null hypothesis and the alternative hypothesis?

A

The null hypothesis is the statement of NO relationship occurring. The alternative hypothesis is when there is a relationship.

(It’s annoyingly called alternative as it is the alternative to the null hypothesis but it is your actual hypothesis)

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3
Q

What is the dependent variable?

A

What is being measured. e.g. how many balls a person gets in the bucket.

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4
Q

What is the independent variable?

A

The thing being changed/manipulated. Normally this is the two different conditions of the experiment e.g. audience or no audience.

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5
Q

What is operationalisation?

A

Making the variables measurable and precise. e.g. instead of “people with an audience will throw more balls in a bucket”, you could operationalise it like this - “people with an audience of 6 people will throw more tennis balls into a 40cm diameter bucket from 2m away”

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6
Q

What is an extraneous variable?

A

A “nuisance” variable that might affect your dependent variable e.g. the colour of the room or the ball skill of the participants.

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7
Q

What is a standardised procedure?

A

Using exactly the same method and instructions for all the participants in your study.

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8
Q

What is randomisation?

A

This is simply randomising things in your experiment e.g. randomly allocating participants into the different groups or giving participants words in a random order for a memory experiment for example.

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9
Q

What is the difference between quantitative and qualitative data?

A
Quantitative = numerical data = easy to analyse lots of it
Qualitative = word data e.g. transcript of an interview = harder and more time consuming to analyse but richer, deeper data
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10
Q

What is a lab experiment and + & - of them?

A

An experiment done in a lab!
+ Highly controlled therefore less extraneous variables
- Not very true to real life, therefore low external validity

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11
Q

What is a field experiment and + & - of them?

A

An experiment done in a realistic setting.
+ Not so easy to control therefore more extraneous variables
- True to real life, therefore high external validity

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12
Q

What is a natural experiment and + & - of them?

A

An experiment where you take advantage of (and therefore don’t manipulate or create) an independent variable that has already happened. e.g. the effects of a hurricane on stress levels. The independent variable is hurricane or no hurricane so you can take advantage of one that has happened (you wouldn’t create a hurricane yourself!)

+ Normally very real life situations
- Don’t happen very often - can be difficult to find

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13
Q

What are the 3 experimental DESIGNS?

A

Independent groups, repeated measures, matched pairs.

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14
Q

What is independent groups and + & -

A

Split your participants into different groups for each level of the independent variable. e.g. half with audience, half without audience.

+ No order effects
- Participant variables can be a problem (e.g. you might end up with all the basketball pros in one group!)

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15
Q

What is repeated measures and + & -?

A

All participants go through all the conditions of the experiment

+ Eliminates participant variables (the basketball pros do both conditions!)
- Order effects - participants may be tired or bored when they have to do the experiment for the second time so the second condition might suffer. Therefore depends which order they do the conditions in.

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16
Q

What is matched pairs and + & -?

A

Pairs of participants are matched on a characteristic relevant to the experiment (e.g. ball throwing ability). One member of each pair does one condition and the other does the other condition.

+ Reduces participant variables
- Very time consuming as you have to measure the characteristic and then do the matching before you even start the experiment.

17
Q

What is counterbalancing?

A

This is when you are doing a repeated measures design to reduce order effects. Half the participants do condition A then condition B. The other half to B first, then A.

18
Q

What is the difference between a target population and a sample?

A

The target population is the entire population you are looking at (and this could just be the population of the world!) e.g. effects of counselling on anxiety in the UK, the target population would be ALL anxious people in the UK.

You obviously couldn’t test EVERYONE so the sample is the people who do your experiment and can be a small sample e.g. 10 or could be a large sample e.g. 1,000 (often in the case of something like a questionnaire)

19
Q

What is random sampling and + & -?

A

Take all the names of the people in your target population, give them all a number, put all the numbers in a hat (or computer) and randomly take out the amount needed.

+ No bias, everyone has a chance of being selected
- Time consuming to get the names of the entire target population and they might not even consent when you contact them

20
Q

What is opportunity sampling and + & -?

A

The researcher selects people who happen to be there at the time.

+ Easy, cheap and quick!
- May not be a representative sample of your target population. Historically most participants of psychology experiments have been university students.

21
Q

What is systematic sampling and + & -?

A

Taking every e.g. 5th, 10th or 20th name of a list of your target population.

+ Avoids researcher bias. Everyone has a chance of being selected.
- There is a small chance that you end up with a biased sample e.g. all men. Also time consuming getting list of entire target population.

22
Q

What is stratified sampling and + & -?

A

Participants are selected from different sub-groups (strata) of the target population in proportion e.g. few managers, lots of factory floor workers

+ Very representative of the target population
- Very time consuming