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research methods Flashcards

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1
Q

what is order effects?

A

happens when participants response in the various conditions are effects by the order of the tasks to which they are exposed to. Either due to boredom, practice or tiredness

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2
Q

how to control order effects?

A

use counterbalancing

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3
Q

what is counterbalancing?

A

the participant sample are split into 2 groups. one group will do the task as task A then task B and the other group will do the tasks as task B then task A. any order effects should be balanced out

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4
Q

types of ethical issues

A

confidentiality, right to withdraw, informed consent, protection for harm, deception

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5
Q

what is confidentiality?

A

. confidentiality is a legal right
. personal info must be protected
. must not beindividually identifiable

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6
Q

how to deal with confidentiality?

A

refer to people through numbers/ letters and dont use participants names

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7
Q

what is right to withdraw?

A

. participants must be told they can withdraw at any point
. if asked to leave- all data about participant must be destroyed

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8
Q

how to deal with right to withdraw

A

. destroy all data if they want to leave
. parent/ guardian of anyone under 16 or mentally disabled ha the right to withdaw them

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9
Q

what is informed consent?

A

. participant should know about all of the information that may influence their willingnes to take part
. anyone under the age of 16 or mentally impaired need parent or guardian to consent for them

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10
Q

how to deal with informed consent

A

Prior consent- tell participants the basic details before the study takes place and that they may be deceived
Presumptive consent- similar group gets told all of the details and asked if they would participant. If they say yes it is presumed the actual participants will say yes.
Retrospective consent- get told the information after they have taken place in the study. If they dont want to participant data is destroyed.

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11
Q

What is protection from harm?

A

Participants must leave in the same or better mental state than they had when they entered the study.

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12
Q

How to deal with protection from harm

A

Have a debrief session and offer counselling if necessary. If harm is noticed, study must stop.

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13
Q

What is deception?

A

. Participants are intentionally lied to
. Deception should only occur in the benefits outweighs the consequences and there is no alternative

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14
Q

How to deal with deception

A

Debrief them at the end and tell them they were deceived for the purpose of the investigation

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15
Q

What is an independent variable?

A

The thing that is manipulated

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16
Q

What is a dependent variable?

A

The thing that is measured

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17
Q

What is operationalising?

A

It helps to develop a clear defined variable

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18
Q

Example of operationalising

A

‘Time of day effects mood’
. IV operationalised- peoples moods at 7am compared to 7pm
. DV operationalised- do a questionnaire to rate mood

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19
Q

What is a alternative hypothesis

A

A precise testable statement that predicts a difference in relationships

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20
Q

What is a null hypothesis

A

A statement that predicts there will be no relationship between factors in investigation

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21
Q

What is a directional hypothesis

A

A hypothesis that has a direction

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22
Q

What is a non directional hypothesis

A

You think there will be a relationship but you dont know the direction

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23
Q

What is an extraneous variable

A

Any variable that is not the independent variable which if left uncontrolled will impact the dependent variable

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24
Q

Types of extraneous variables

A

Participant variables, order effects, investigator effects, demand characteristics, social desirability, screw u effect

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25
Q

What is participant variables

A

Participants all have differences so this can decrease validity. To deal with it use random allocation

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26
Q

What is order effects

A

In repeated measures, participants may get bored or over practiced so decrease validity. To deal with this can do counterbalancing.

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27
Q

What is investigator effects

A

Where an investigator may have certain behaviours which may lead to people finding out the aims of the study. To reduce this do a double bind test.

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28
Q

What is demand characteristics

A

Where they may find cues to reveal the aim or purpose of the study.

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29
Q

What is social desirability

A

Where people may answer questions in a way which they think may present them in a better light. To deal with this use a single bind test.

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30
Q

What is the screw u effect

A

People may intentionally underperform to sabotage the study

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31
Q

Types of experiments

A

Lab experiment, field experiment, quasi experiment, natural experiment

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32
Q

lab experiments

A

. It involves the direct manipulation of independent variables to see effect on dependent
. participants know they are being studied
. Cause and effect is established
. Carefully controlled conditions
. Extraneous variables can be controlled
. Can be randomly allocated

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33
Q

Field experiments

A

. Involves direct manipulation of IV to see impact on the DV
. Real world everyday setting
. Cause and effect can be established
. Extraneous variable can be difficult to control
. Can be randomly allocated
. Dont know they are being studied

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34
Q

Quasi experiment

A

. Cause and effect can not be established
. Can be either in a lab or in real world everyday setting
. Often know they are being studied
. Cannot be randomly allocated
. Extraneous variables can be hard to control
. The IV has not been made to vary by anyone

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35
Q

Natural experiment

A

. Cause and effect cannot be established
. Either in a lab or in real world setting
. Often know they are being studied
. Cannot be randomly allocated
. Extraneous variable can be hard to control
. The researcher does not manipulate the IV directly

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36
Q

Pros and cons of lab experiment

A

Pros:
. Easy to replicate
. Control extraneous variables

Cons:
. Lacking ecological validity
. Increased risk of demand characteristics

37
Q

Pros and cons of field experiments

A

Pros:
. Ecological validity
. Avoiding participant reactivity

Cons:
. Raises ethical issues
. Lack of control of extraneous variables

38
Q

Pros and cons of natural experiment

A

Pros:
. More ethical
. High external validity

Cons:
. Hard to replicate
. Lack of control of participant variables

39
Q

Pros and cons of quasi experiment

A

Pros:
. Controlled conditions
. Less ethical problems

Cons:
. Can not randomly allocate participants
. Causal relationship not demonstrated

40
Q

Types of experiment design

A

Repeated measures design, independent group design, matched pairs design

41
Q

What is repeated measures design

A

Same participants do both conditions

42
Q

What is independent group designs

A

Different participants do one condition each

43
Q

What is matched pair design

A

Use different but similar participants in different conditions. Matched due to have similarities

44
Q

Pros and cons of repeated measures design

A

Pros:
. No participant variable

Cons:
. Problem with order effects

45
Q

Pros and cons of independent group design

A

Pros:
. No order effects

Cons:
. Participant variables

46
Q

Pros and cons of matched pair design

A

Pros:
. No order effects

Cons:
. Hard to match pairs

47
Q

What is population

A

The large group of people that a researcher is interested in studying for example college students in the north west

48
Q

What is sampling

A

Usually not possible to include all members of the population in the study so a smaller group is selected

49
Q

What is generalisation

A

Sample is drawn which should be representative of the population so generalisation can be made

50
Q

What is bias

A

Most samples are biased in that certian group.

51
Q

Random sampling

A

Everyone has an equal chance of being picked. Use a random name generator to collect participants. Pros- unbiased so EVs are controlled, enhancing validity. Cons- time consuming, complete list of population is hard and some may refuse to take part

52
Q

Systematic sampling

A

Participants are selected using a set pattern. Use every nth number. Pro- unbiased as the first item is usually unbiased so is objective method. Cons- time and effort as a complete list is required so may as well use random sampling

53
Q

Staratified sample

A

Sample reflects proportions of people in subgroups. Relative percentages of the subgroups in the population are reflected in the sample. Representative method- the characteristics of the target population are represented. So more able to generalise. Not perfect- doesnt always reflect everyone equally so complete representation isnt possible.

54
Q

Opportunity sample

A

People who are simply most available. Ask people nearby. Pros- quick method as they use people readily available. Cons- biased as the sample is unrepresentative so cant be generalised

55
Q

Volunteer sample

A

Select themselves. Pros- participants are willing so will be know how much much home and effort is involved. Likely to engage. Cons- volunteer bias as they nominate themselves they share certian characteristics so cant be generalised.

56
Q

Correlation

A

Illustrates the strength and direction of an association between two co variables

57
Q

Scattergram

A

One co-variable is on the x axis the other is on the y axis

58
Q

Types of correlation

A

Positive correlation, negative correlation and no correlation

59
Q

Difference between correlations and experiment

A

In an experiment the researcher manipulates the iv and records the effect on the dv. In correlation there is no manipulation of variables so cause and effect cant be established

60
Q

Strengths of correlation

A
  1. Useful starting point as it assesses the strength and direction of a relationship. Shoes how 2 variables are related. If variables are strongly correlated it may suggest hypotheses for future studies.
  2. It is relatively economical as there is no need for a controlled environment and it can be secondary data so correlation can be less time consuming that an experiment
61
Q

Limitations of correlations

A
  1. Cant establish cause and effect as it shows a relationship but it is described as causal meaning there is a link but not a cause and effect so can lead to false conclusions about causes of behaviours.
  2. Intervening variables is where another untested variable may explain relationship between the co variables therefore may lead to false conclusions
62
Q

Qualitative data and strengths and limitations

A

Non numerical data expressed in words
Strength:
- richness is detailed so it gives a much broader scope than quantitative data so is more meaningful with greater external validity
Limitation:
- difficult to analyse as it’s hard to identify patterns and make comparisons so leads to subjective interpretation of data

63
Q

Quantitative data and strengths and limitations

A

Numerical data
Strength:
- easier to analyse as you can draw conclusions in graphs and calculations so comparisons can be made between groups
Limitation:
- narrower in meaning as there is less detail as has lower external validity so may be less like real life

64
Q

Primary data and strengths and weaknesses

A

First hand data collected for study
Strength:
- fits the job as data is collected for the study so information is directly related
Weakness:
- requires effort as designing and collating questionnaires takes time and expense so is time consuming

65
Q

Secondary data and strengths and weaknesses

A

Collected by someone other than the person who is conducting the research
Strength:
- inexpensive as the desired information already exists so requires minimal effort
Weakness:
- quality may be poor as information may be outdated which challenges the validity of any conclusions

66
Q

Meta analysis and strengths and weaknesses

A

A types of secondary data that involves combining data from a large number of studies
Strength:
- increases validity of conclusions the eventual sample size is much larger than individual samples which increases the extent of generalisation
Weakness:
- publication bias as researcher may not select all relevant studies leaving out negatives therefore may lack validity

67
Q

mean strengths and weaknesses

A

strength:
it is a sensitive measure. it includes all the values in the data set which makes it more representative
weakness:
it may be unrepresentative as extreme values can distort the calculation.

68
Q

median strengths and limitations

A

strength:
less affected by extreme values. this is because it is only focused on the middle value so is more representative for the whole group
weakness:
it is less sensitive than the mean. this is because the extreme results are ignored. the extreme values may be very important to the study

69
Q

mode strengths and weaknesses

A

strength:
relevant to categorical data. when data is discrete this is the only appropriate measure to use, so is applicable to all.
weakness:
it is too oversimplified as the mode may be one of the extreme values. not they best at describing data when there are many modes.

70
Q

range strengths and weaknesses

A

strength:
it is easy to calculate as you just subtract the smaller value from the large value.
weakness:
it doesn’t account for distribution. it doesn’t indicate how close the values are to each other so could be spread out or anomalies. standard deviation is better as it shows the dispersion of data.

71
Q

standard deviation strengths and weaknesses

A

strength:
it is more precise than the range as it includes all of the values. therefore it gives a more accurate picture of the distribution of the data set.
weakness:
it may be misleading as it can be distorted by extreme values. this means that the extreme values wont be revealed unlike with the range

72
Q

types of distribution skews

A

positive skew and negative skew

73
Q

what is a negative skew

A

where the mean is lower than the median or mode, meaning the curve is going towards the right

74
Q

what is a positive skew

A

when the mean is higher than the median and mode, meaning the curve goes towards to the left

75
Q

what is a correlation

A

it shows the relationship or an association between 2 continuous variables

76
Q

what is a correlation coefficient

A

the strength of the correlation between -1 and 1. the closer to 1 (-1 or 1) the stronger the correlation. the closer to zero the weaker the correlation.

77
Q

what is reliability

A

the measure of consistency. show that all studies have had the same/similar results

78
Q

how to test reliability

A

. test retest method- do the original test then give them the same/something very similar and compare results
. interobserver- 2 or more observers should carry out a pilot study and take separate data and then compare.
. using correlation- from using the test retest method and interobserver techniques, the correlation coefficient should be +0.8 or more for reliability

79
Q

how to improve reliability

A

. by using questionnaires and rewriting some of the questions (making them open ended)
. improve the training of interviewers so they avoid leading or ambiguous questions.
. operationalise the behaviour categories- this is to avoid overlapping or gaps
. standardised procedures- the procedure should be the same for all participants every time

80
Q

what is validity

A

if the observed effect is genuine and represents what is actually being found. data can be reliable but not valid as it may be consistent however not true.

81
Q

types of validity

A

. internal validity- control within the study e.g. demand characteristics
. external validity- generalising in other areas or populations
. ecological validity- whether it can be applied from one setting to another in everyday life
. temporal validity- finding should be consistent over time.

82
Q

ways of assessing validity

A

. face validity- a test looks like it measures what it claims to. this is done by simply eyeballing or by passing it to an expert to check
. concurrent validity- whether findings are similar to those on a well established test. correlation should be +0.8 for validity

83
Q

how to improve validity

A

. using a control group- this will mean that the researcher is sure that the changes in DV due to the manipulation in the IV. can also use a double bind test
. lie scale- helps to control social desirability
use good categories- do this by operationalising so its not ambiguous

84
Q

what are statistical tests used for

A

to checking there is cause and effect and not due to chance

85
Q

the criteria for statistical test

A
  1. difference or association?
  2. related (RM or MP) or unrelated (IG)?
  3. nominal, ordinal, interval?
86
Q

what nominal data

A

categories e.g. what’s your favourite football team?

87
Q

what’s ordinal data

A

can be placed in an order however its subjective e.g. ranking on a scale 1-10

88
Q

what’s interval data

A

units of equal precisely defined sizes e.g. how tall are you in feet and inches?

psychology (12 decks)

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