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rsm Flashcards

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1
Q

what is an aim

A

a statement of the study’s purpose.
should be stated beforehand so it is clear what the study intends to investigate

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2
Q

What is a one-tailed (directional) hypothesis

A

a hypothesis that predicts a difference between your variables. it makes a directional prediction e.g. higher or lower

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3
Q

when would you use a one tailed hypothesis

A

when you have previous research findings which suggest which way the results will go

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4
Q

what is a two-tailed (non directional) hypothesis

A

a hypothesis that predicts a difference but doesn’t state where the difference lies

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5
Q

when you you use a two tailed investigation

A

when there is no or little previous research in the area or when results are mixed or inconclusive

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6
Q

what is a null hypothesis

A

this is what you assume is true during the study. any satay you collect will either back this assumption or it won’t. if the data doesn’t support you null hypothesis, you reject it and go with your alternative hypothesis instead

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7
Q

what is a typical null hypothesis

A

the null hypothesis will predict that there is no difference/ relationship between your variables

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8
Q

what is a bar chart

A

used to present non-
continuous data

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9
Q

how is a bar chart different to a histogram

A

columns do not touch

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10
Q

what is a histogram

A

used when you have continuous data- the columns touch and it is the height of the column that shows the number of values in each interval

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11
Q

what is correlational analysis

A

a measure of how closely two variables are related

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12
Q

what are advantages of correlational analysis

A

-do not need to use a controlled experiment
-can use sensitive data obtained from hospitals e.g

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13
Q

what are disadvantages of correlational analysis

A

-cannot establish cause and effect- third variable
- coefficients can be due to chance, may be other unknown variables or extraneous variables that may lead to false conclusions

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14
Q

what is correlation coefficient

A

a number between -1 and +1 = the closer it is, the stronger the relationship between the variables

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15
Q

correlations

A

positive correlation- as one variable rises the other rises

negative correlation- as one variable rises the other falls

no correlation- the variables are not linked

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16
Q

what is normal distribution

A

a symmetrical spread of frequency data that forms a bell-shaped pattern
the mean, medium and mode are all located at the highest peak

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17
Q

what is skewed distribution

A

a spread of frequency data that is not symmetrical where the clusters to one data

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18
Q

negative distribution

A

a type of distribution in which the long tail is on the negative (left) side of the peak and most of the distribution is concentrated on the right

the mode is more than the median which is more than the mean

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19
Q

positive distribution

A

a type of distribution in which the long tail is on the positive (right) side of the peak and most of the distribution is concentrated on the left

the mode is less than the med, which is less than the mean

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20
Q

what is the independent variable

A

the variable directly manipulated by the researcher ( what you are changing)

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21
Q

what is the dependent variable

A

the variable you think will be affected by the changes in the IV

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22
Q

what is meant by operationalisation

A

describing the process by which the variable is measured. this allows other researchers to see exactly how you are defining and means your variables

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23
Q

random allocation

A

everyone has an equal chance of doing either condition

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24
Q

counterbalancing

A

mixing up the order of the tasks. this he,ps with order effects in repeated measures designs

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25
Q

randomisation

A

when materials are presented to the participants in random order

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26
Q

standardisation

A

everything should be as similar as possible for all the participants

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27
Q

what are extraneous variables

A

any variable (other than the IV) that could affect what you’re trying to measure

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28
Q

how can extraneous variables be controlled

A

random sampling creates more equality between groups

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29
Q

confounding variables

A

any variables that influences your DV

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30
Q

validity

A

accuracy- internal and external

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31
Q

ecological validity

A

generalisable to real life settings

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32
Q

concurrent validity

A

results from the new test can be compared to previously well-established test

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33
Q

population validity

A

whether you can reasonably generalise the findings from your sample to a larger group of people

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34
Q

temporal validity

A

assesses to what degree research findings remain over time

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35
Q

face validity

A

the extent to which a test appears to measure what is intended to measure

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36
Q

what is reliability

A

the overall consistency of a measure

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37
Q

what is internal reliability

A

the extent to which a test is consistent within itself

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38
Q

external reliability

A

the ability of the test to produce the same results each time it is carried out

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39
Q

what are ethical guidelines

A

ethical guidelines were developed for psychologists to follow when they are designing studies so that participants are protected

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40
Q

informed consent

A

participants should always give informed consent (under 16 by parents or guardians) they should be told the aims and nature of the study and the right to withdraw

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41
Q

deception

A

if participants have been deceived then they cannot give informed consent. sometimes researchers must withhold information about the study because the participants would not behave naturally if they knew what the aims were

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42
Q

right to withdraw

A

participants are allowed to withdraw from the research at any point

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43
Q

confidentiality

A

none of the participants in the study should be identifiable from any reports that are produced. data must be confidential and anonymous

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44
Q

protection from harm

A

risk of harm to participants in the study should be no greater than they would face in their normal lives

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45
Q

what is a debrief

A

this should return participants to the state they were in before the researcher. researchers must fully explain what the research involved and what the results might show

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46
Q

what are independent groups

A

there are different participants in each group

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47
Q

what is an advantage of independent groups

A

no order effects

fewer demand characteristics

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48
Q

what are weaknesses of independent groups

A

participant variables- individual differences

number of participants- twice as many

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49
Q

what are repeated measures

A

all participants do all conditions
used to compare each condition to each other

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50
Q

advantages of repeated measures

A

participant variables

number of participants

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51
Q

weaknesses of repeated measures

A

order effects

demand characteristics

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52
Q

what are matched pairs

A

there are different participants in each condition but they are matched on important variables

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53
Q

matched pairs advantages

A

no order effects

participant variables

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54
Q

matched pairs weaknesses

A

number of participants

practicalities- time consuming and difficult to find people who match

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55
Q

what is the nature and use of a field experiment

A

experiments conducted outside of the lab. behaviour is measured in a natural environment such as a school. a key variable is still altered so it’s effect can be measured

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56
Q

advantage of a field experiment

A

casual relationship

ecological validity

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57
Q

weaknesses of field experiments

A

less control

ethics

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58
Q

what is the nature and use of a laboratory experiment

A

an experiment that controls all relevant variables except one key variable, which is altered to see to what the effect is

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59
Q

what are advantages of lab experiments

A

controlled

replicable

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60
Q

what are weaknesses to laboratory experiments

A

artificial

demand characteristics

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61
Q

what is a confederate

A

someone who is involved in the research that tries to influence the participants

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62
Q

what is an experimental group

A

the participants are the experiment who the researcher is testing e.g. they may receive a drug

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63
Q

what is a control group

A

the other condition where participants are taking part in the experiment but no manipulation is used. e.g. they may receive a saline solution instead of the drug that the experimental group received

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64
Q

what are demand characteristics

A

participants may have determined the aims of the study
they might act deliberately to please the researcher or the opposite

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65
Q

how can demand characteristics be controlled

A

counterbalancing / randomisation

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66
Q

what is a double blind experiment

A

neither the participants or the researchers know which condition the participants are in
this use used in medical trials

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67
Q

what is a single blind experiment

A

the participants do not know what condition they are in
used for experiments and control groups

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68
Q

what is the nature and use of a natural experiment

A

where the researcher look at how the IV, which is not manipulated by the researcher, effects the DV. the IV is an event that occurs naturally
for example, single sex schools and mixed schools

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69
Q

advantages of natural experiments

A

demand characteristics

ecological validity

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70
Q

weaknesses of natural experiments

A

casual relationship

ethics

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71
Q

what is the nature and use of quasi experiments

A

the researcher is not able to use random allocation to put participants into different conditions. naturally occurring IV, for example, biological sex

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72
Q

advantages of quasi experiment

A

control

ecological validity

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73
Q

disadvantages of quasi

A

participant allocation

casual relationship

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74
Q

what are behavioural categories

A

categories defined by the researcher to observe during the experiment
for example aggression in children

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75
Q

what is event sampling

A

researcher records every event (if a behaviour category) when observed in research

76
Q

what is time sampling

A

researcher records every behaviour within a certain time frame

77
Q

what is a controlled observation

A

takes place in a laboratory so the researcher can control the conditions

78
Q

what are strengths of controlled observation

A

replication is possible due to highly controlled procedures

extraneous variables can be controlled

79
Q

what are weaknesses of controlled observations

A

lower ecological validity

participants may alter their behaviour if they know they are being observed

80
Q

what is naturalistic observation

A

takes place in a natural environment
they can be structured in advance to make sure no behaviours as missed

81
Q

what are strengths of naturalistic observation

A

ecological validity

theory development

82
Q

what are weaknesses of naturalistic observation

A

extraneous variables

observer bias

ethics

83
Q

what is covert observation

A

researchers presence is unknown to the participants

84
Q

what are strengths of covert observation

A

the participants are more likely to act naturally

85
Q

what is a weakness of covert observation

A

gaining ethics can be difficult

86
Q

what is overt observation

A

researchers presence is obvious to participants

87
Q

strengths of overt observation

A

more ethically sound than other methods because the participants are aware of the research

88
Q

weaknesses of overt observation

A

people might change their behaviour if they know they are being observed

89
Q

what is participant observation

A

when the researcher participants in the study

90
Q

strengths of participant observation

A

the researcher develops a relationship with the group in the study

91
Q

weaknesses of participant observation

A

the researcher loses objectivity by becoming part of the group

the participants might act differently if they know there is a researcher amongst them

92
Q

what is non participant observation

A

when the researcher observes the activity without getting involved in it

93
Q

strengths of non participation

A

the researcher can remain objective throughout the study

94
Q

weaknesses of non participation

A

the researcher loses a sense of the group dynamics by staying separate from the group

95
Q

what is structured observation

A

the researcher gee determines precise what behaviours are to be observed and uses a standardised checklist to record the frequency with which they are observed within a specific time frame

96
Q

strengths of structured observation

A

controlled

can be repeated

97
Q

weaknesses of structured observation

A

might miss relevant information if too controlled

98
Q

what is unstructured observation

A

the observer recalls all relevant behaviour but has no system

99
Q

strengths of unstructured

A

all behaviour is recorded

100
Q

weakness of unstructured

A

not controlled or repeatable

101
Q

what is inter-rather reliability

A

the test should give consistent results regardless of who administers it. this can be assessed by correlating the scores that each researcher produces and comparing them. consistenty is key

102
Q

what is the nature and use of an interview

A

used to gather qualitative research- can be face to face or over the phone

103
Q

what are advantages of interviews

A

rich data

pilot study

104
Q

what are weaknesses of interviews

A

impractical

ethics

105
Q

what is a structured interview

A

fixed set of questions that are the same for all participants

106
Q

what are strengths of structured interviews

A

can be easily repeated

requires less skill

easier to analyse

107
Q

weaknesses of structured interviews

A

interview bias can still occur

social desirability

data collection is restricted by pre determined questions

108
Q

what is the nature and use of a unstructured interview

A

the interview starts with some general aims and questions and then let’s the interviewees answers guide subsequent questions

109
Q

strengths of unstructured interviews

A

Detailed information can be obtained
High validity – good rapport
Deeper insight into thoughts and feelings

110
Q

weaknesses of unstructured interviews

A

• Interviewer bias
• Requires training
• Harder to analyse

111
Q

what are investigator effects

A

These can be anything that the researcher does which can affect how the participant behaves. If a researcher’s expectations influence how they behave towards their participants, the participants might respond to demand characteristics.

112
Q

what is researcher bias

A

researchers’ expectations can influence how they design their study and how they behave towards the participants. Their expectations may influence how they take measurements and analyse their data, resulting in errors that can lead, to accepting a hypothesis that is actually false.

113
Q

how can you avoid investigator effects

A

A research assistant can conduct the research using standardised procedures to avoid bias/ effects.

114
Q

what is content analysis

A

Research analysing secondary data and data you have already collected. Data is split into categories.

115
Q

describe the process involved in content analysis

A

A representative sample of qualitative data is collected, for example, from an interview, magazine Coding units are identified to analyse the data. A coding unit could be, for example, an act of violence. The qualitative data is then analysed to see how often each coding unit occurs.

116
Q

on what type of data is content analysis used

A

secondary data

117
Q

strengths of content analysis

A

• Inexpensive
• Ethics – participants are not directly involved, so less ethical issues.

118
Q

weaknesses of content analysis

A

• Data analysis- can be very time consuming • Subjectivity

119
Q

what is thematic analysis

A

making summaries of data and identifying key themes and categories. • The researcher becomes familiar with the data. Then they start to look for different themes,
review the themes, define and name the themes and then write a report.

120
Q

strengths of thematicanalysis

A

• Qualitative data preserves the detail in the data
• Creating hypotheses during the analysis allows for new insights to be developed
• Some objectivity can be established by using triangulation – other sources of data are used to check conclusions

121
Q

weaknesses of thematic analysis

A

• Deciding which categories to use and whether a statement fits a particular category
• Deciding what to leave out of the summary- data can be lost
• Subjective

122
Q

how is the mean calculated

A

Adding all the scores in a data set and then dividing by the number of scores.

123
Q

advantages of mean

A

Uses all scores in the data
It is a very sensitive statistic because it takes account of the exact distance between all the values of all the data

124
Q

weaknesses of mean

A

If one of the values is extremely high or low (anomalous), then the overall mean can be very distorted and therefore misrepresent the data.
• It cannot be used with nominal data

125
Q

what is mode

A

The score that occurs most often

126
Q

what are strengths of mode

A

Shows the most common score
• Unaffected by extreme values and is
useful for discrete data and is the only method which can be used for nominal data.

127
Q

what are weaknesses of mode

A

Sometimes there are so many modes that the data cannot be described using this statistic.
• Has little further use in data analysis

128
Q

how is the median calculated

A

the middle score when the data is put in order

129
Q

strengths of median

A

It’s quick and easy to work out
• It is not affected by extremely high or low scores

130
Q

weaknesses of median

A

Not all the scores are used to work out the median

131
Q

what is the range

A

highest score minus the lowest score

132
Q

advantages of range

A

it is easy and quick to calculate

133
Q

weaknesses of range

A

it completely ignores the central values of data set, so it can be misleading if there are very high or low scores

effected by extreme values

134
Q

what is the standard deviation

A

measures on average how much scores deviate from the mean

135
Q

advantages of standard deviation

A

all scores in the set are considered so it is more accurate than the range

136
Q

weaknesses of standard deviation

A

it is not quick or easy to calculate

137
Q

what is qualitative data

A

data involving words, videos or audio

138
Q

what is quantitative data

A

numbers

139
Q

what is primary and secondary data

A

Primary data is data collected first hand by the researcher. Secondary data is data collected from a source such as a book or newspaper (national statistics).

140
Q

what is meta analysis

A

this is where you analyse the results from loads of different studies and come up with some general conclusions

141
Q

what is a pilot study

A

a ‘feasibility’ study, is a small-scale preliminary study conducted before any large-scale quantitative research in order to evaluate the potential for a future, full-scale project. Pilot studies are a fundamental stage of the research process. Pilot studies allow researchers to check the methodology, standardise the instructions and allow the research can be conducted.

142
Q

what is the nature and use of a questionnaire

A

can be written, face to face, on the phone or online

143
Q

what is the design of questionnaire

A

open questions are questions that allow the participants to respond in any way and in as much detail as they like. This gives detailed, qualitative information. Closed questions limit the answers that can be given. They give quantitative data which is easier to analyse.

144
Q

what are advantages of questionnaires

A

Practical – you can collect a lot of data

145
Q

disadvantages

A

• Bad questions – leading questions or unclear questions can be a problem
• Biased samples
• Self-report

146
Q

what is social desirability

A

People usually try to show themselves in the best possible light. They might not be completely truthful
but give answers that are more socially acceptable.

147
Q

how does social desirability affect validity

A

Not a true representation of someone’s opinions/ thoughts/ feelings.

148
Q

what is the nature and use of case studies

A

case studies have intensive descriptions of a single individual or case. Case studies allow researchers to analyse unusual cases in a lot of detail.

149
Q

what are the advantages of case studies

A

rich data

unique cases

150
Q

what are weaknesses of case studies

A

Causal relationship – cause and effect cannot be established
Cannot be generalised

151
Q

what is a sample

A

a representative group of people from a target population

152
Q

what is meant by a population

A

All the people in a particular group- for example, a certain age or
background

153
Q

what is random sampling

A

this is when every member of a target group has an equal chance of being selected for the sample. This could be done either manually or by a computer.

154
Q

what are advantages to random sampling

A

Fair – everyone has a chance of being selected
Sample is likely to be representative

155
Q

what are weaknesses of random sampling

A

Not guaranteed to have a representative sample
The researcher may end up with a biased sample because the sample is too small.

156
Q

what is a volunteer sampling

A

this is when people actively volunteer to be in a study by responding to a request for participants advertised by the researcher, for example, in a newspaper or on a notice board.

157
Q

what are advantages of volunteering

A

A large number of people may respond • In-depth analysis and accurate results if
larger sample

158
Q

what are weaknesses of volunteering

A

Not representative- only sample of
people who have responded

159
Q

what is opportunity sampling

A

when the researcher samples whoever is available and willing to be studied. Since many researchers work in universities, they often use opportunity samples made up of students

160
Q

what are advantages of opportunity sampling

A

quick and practical

161
Q

what are weaknesses in opportunity sampling

A

Unlikely to be a representative sample
• Cannot generalise the findings

162
Q

what is stratified sampling

A

this is where important subgroups in the population, for example, different age groups, are identified and a proportionate number of each is randomly obtained. For example, in a class of 20 students, ten are 16 years old, eight are 17-year olds, and two are 18 years old. If you take a stratified sample of 10 students, the number of 16-, 17- and 18- year-olds in the sample needs to be 50% of the full class. You would need five 16-year olds, four 17-year olds and one 18-year-old in your sample.

163
Q

what are advantages of stratified sampling

A

Fairly representative sample

164
Q

what weaknesses of stratified

A

• It is time-consuming because all potential participants need to be assessed and categorised.
• Some groups within a sample may not be represented if a small sample is used

165
Q

what is systematic sampling

A

this is where every nth name from a sampling frame (a record of all the names in a population) is taken, for example, every 3rd name from a register, or every 50th name from a phone book.

166
Q

advantages of systematic sampling

A

Simple and effective way of generating a sample with a random element
• Population is more likely to be evenly sampled

167
Q

weaknesses of systematic sampling

A

Subgroups might be missed
• Not necessarily representative if the pattern used for the sample coincides with a pattern in the population.

168
Q

what are alternative ways of getting consent

A

Presumptive consent: ask a similar group of people for consent.
Prior general consent: consent for different studies, including one that may involve deception. Retrospective consent: ask for consent during debrief.

169
Q

what is nominal data

A

data represented in the form of categories. For example, how many students in the 6th form drive to school, how many walk etc.
Nominal data is discrete, one item can only appear in one category.

170
Q

what is ordinal data

A

data which is ordered in some way. Ask everyone in the class how much they like the 6th form on a scale of 1 – 10.
Ordinal data does not have equal intervals between each unit. It would not make sense to say that someone who rated the 6th form as an 8 enjoys it twice as much as someone who rated it 4.

171
Q

what are interval/ratio data

A

is based on numerical scales that include units of equal precisely defined size. Units of measurements for height, time and temperature for example.

172
Q

how to do statistical testing

A
  1. Null hypothesis – this is the prediction you want to test - You assume the null hypothesis is true
  2. Significance level – this is the level of proof you are looking at before you read into your results
    - The smaller the significance level the stronger the evidence you’re looking for that your
    results are not just down to chance.
    - A significance level is a probability and the number is between 0 and 1
    - Significance levels are very small- usually 0.05 or less.
  3. You turn your experimental results into a single statistics test
    - You can find out what the probability is that this test statistic and your results were the
    results of a fluke (making your null hypothesis true)
  4. If the probability of your results being a fluke is less than the significance level, you can suggest
    that your null hypothesis was not true. You can then assume that the difference between groups was down to the change your made in your independent variable.
    - You reject the null hypothesis and assume your alternative hypothesis is true
  5. Your results are therefore statistically significant (if you reject the null hypothesis)
  6. If you do not reject the null hypothesis, it means that your results could have occurred by
    chance
  7. Using a significance level of 0.05 is suitable for most tests
    - If the probability of your results being down to chance is less than or equal to (p≤ 0.05) then it is good evidence that the null hypothesis was not true.
    - You are 95% confident in your conclusion
    - If you use a significance level of 0.01, then you have really strong evidence that the null
    hypothesis is not true. The researchers can be at least 99% confident.
173
Q

mann whitney

A
  • test of difference
  • independant group
    -ordinal data- scores
174
Q

wilcoxon

A
  • experimental design can be repeated measures or matched pairs
    -alternative hypothesis
  • there is a difference in people with ocd scores on happiness questionnaire before and after treatment
    null hypothesis- there is no difference in people with ocd scores on a happiness questionnaire before and after treatment
175
Q

spearman’s rho

A
  • two sets of values at an ordinal level
  • its a correlation so we are looking for a relationship
176
Q

pearsons r

A
  • both variables must be interval or ratio and be normally distributed
  • the correlation of the two variables must fall between -1 and +1
  • the closer r is to -1 and +1 the stronger the relationship
    -degrees of freedom N-2
  • a relationship between 2 co variables
177
Q

related t tests

A
  • repeated measures design or matched pairs
  • test of difference with interval or ratio data
178
Q

unrelated t-test

A
  • independant groups
  • interval data is needed
  • test of difference
179
Q

chi squared test

A
  • test of difference or association
  • the data is norminal and recorded as a frequency
    -independent groups design- unrelated
180
Q

features of science

A
  • paradigms and paradigm shifts
  • theory construct and hypothesis testing
  • falsifiability
  • replicability
  • objectivity and the empirical method
181
Q

paradigms and paradigm shifts

A

-kuhn stated that the way to distinguish between scientific and non scientific disciplines is to the shared set of assumptions and methods

-social sciences lack a universally accepted paradigm and should be seen as ‘pre-science’

-progress within an established science occurs when there is a scientific revolution

  • a paradigm shift occurs when there is contradictory evidence to a theory
  • cognitive neuroscience, and behavioural approach, classical and operant conditioning changes what we theorised about behaviour
182
Q

theory construct and hypothesis testing

A

what is a theory?
• a set of general laws or principles that have the ability to explain particular events or behaviours
• theory construction occurs through gathering evidence via direct observations (the empirical method)

what is a hypothesis?
• prediction based on theory
• deduction new hypothesis from an existing theory

183
Q

falsifiability

A

popper ‘genuine scientific theories should hold themselves up for hypothesis testing and the possibility of being proven false’
• even ‘proven’ research is not true, it has just not yet been proven false!
• ‘this supports’ or ‘this seems to support’ and the null hypothesis

184
Q

replicability

A

an element of poppers hypothetical-deductive method
• trusted findings should be repeatable across a number of contexts and circumstances
• validity and reliability

185
Q

objectivity and the empirical methods

A

• ‘critical distance’ - putting away any bias
• controlled laboratory studies
• experience- knowledge is determined only by experience and sensory perception (locke)

research methods psychology (1 decks)

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