research methods Flashcards

Question

What is participant variables

Answer 1

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

Answer 2

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

Answer 3

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.

Answer 4

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

Answer 5

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.

Answer 6

People may intentionally underperform to sabotage the study

Answer 7

Lab experiment, field experiment, quasi experiment, natural experiment

Answer 8

. 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

Answer 9

. 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

Answer 10

. 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

Answer 11

. 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

Answer 12

Pros: . Easy to replicate . Control extraneous variables Cons: . Lacking ecological validity . Increased risk of demand characteristics

Answer 13

Pros: . Ecological validity . Avoiding participant reactivity Cons: . Raises ethical issues . Lack of control of extraneous variables

Answer 14

Pros: . More ethical . High external validity Cons: . Hard to replicate . Lack of control of participant variables

Answer 15

Pros: . Controlled conditions . Less ethical problems Cons: . Can not randomly allocate participants . Causal relationship not demonstrated

Answer 16

Repeated measures design, independent group design, matched pairs design

Answer 17

Same participants do both conditions

Answer 18

Different participants do one condition each

Answer 19

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

Answer 20

Pros: . No participant variable Cons: . Problem with order effects

Answer 21

Pros: . No order effects Cons: . Participant variables

Answer 22

Pros: . No order effects Cons: . Hard to match pairs

Answer 23

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

Answer 24

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

Answer 25

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

Answer 26

Most samples are biased in that certian group.

Answer 27

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

Answer 28

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

Answer 29

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.

Answer 30

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

Answer 31

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.

Answer 32

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

Answer 33

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

Answer 34

Positive correlation, negative correlation and no correlation

Answer 35

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

Answer 36

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

Answer 37

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

Answer 38

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

Answer 39

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

Answer 40

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

Answer 41

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

Answer 42

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

Answer 43

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.

Answer 44

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

Answer 45

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.

Answer 46

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.

Answer 47

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

Answer 48

positive skew and negative skew

Answer 49

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

Answer 50

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

Answer 51

it shows the relationship or an association between 2 continuous variables

Answer 52

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.

Answer 53

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

Answer 54

. 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

Answer 55

. 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

Answer 56

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.

Answer 57

. 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.

Answer 58

. 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

Answer 59

. 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

Answer 60

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

Answer 61

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

Answer 62

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

Answer 63

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

Answer 64

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