Research Methods Flashcards

1
Q

Aims

A

Outline research topic

“To investigate”

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2
Q

Alternative hypothesis

A

A prediction

Directional or non-directional

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3
Q

Directional hypothesis

A

States which way they predict the results will go

Eg boys will score higher on the maths test than girls

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4
Q

Non directional hypothesis

A

States there will be a difference but not what that difference will be
Eg. “There will be a difference in maths test scores between boys and girls”

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5
Q

Null hypothesis

A

This hypothesis is accepted if the results of the experiment are not significant
States that there will be no or any difference is down to chance

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6
Q

Independent variable

A

The thing that is changed or manipulated

Eg the groups or the conditions

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7
Q

Dependent variable

A

The thing that is measured

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8
Q

Operationalised

A

Explaining how the variables could be manipulated/measured

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9
Q

Correlational hypothesis

A

There is not an IV or DV

there are co-variables, 2 things that are measured and compared for a relationship

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10
Q

How many types of sampling and their names

A
5
Systematic 
Stratified 
Opportunist 
Volunteer 
Random
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11
Q

Random sampling

A

Every participant has an equal chance of being selected

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12
Q

Opportunity sampling

A

Asking people who are around at the time to take part

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13
Q

Volunteer sampling

A

Researcher advertises The study and people who see the advert may get in contact and volunteer

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14
Q

Systematic sampling

A

Selecting every nth name from a list

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15
Q

Stratified sampling

A

Selecting people from every portion of your population in the same proportion

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16
Q

Strengths of random sampling

A

> free from researcher bias

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16
Q

Weakness of random sampling

A

> Difficult and time consuming

> unrepresentative

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18
Q

Strength of volunteer sampling

A

Easy to do

Less time consuming

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19
Q

Weakness of volunteer sampling

A

> tend to get similar people taking part (volunteer bias)

> cannot generalise results

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20
Q

Strengths of opportunist sampling

A

> Less time consuming

> And less costly in money

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21
Q

Weaknesses of opportunist sampling

A

> Unrepresentative- usually end up with the same sort of people
Researcher bias

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22
Q

Strength of systematic sampling

A

> avoids researcher bias

> usually fairly representative

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23
Q

Weakness of systematic sampling

A

> can be unrepresentative

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24
Q

Strength of stratified sampling

A

Clear representation of each portion of population

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25
Q

Laboratory experiment

A

> Artificially controlled environment
Independent variable is manipulated
Participants are randomly assigned to conditions

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26
Q

Weakness of stratified sampling

A

Difficult and time consuming

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27
Q

Strengths of the laboratory experiment

A

> Higher internal validity due to control,over extraneous variables
easy to replicate

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28
Q

Weakness of laboratory experiment

A

> Artificial environment - less generalisable

> Low external validity as it may bring out demand characteristics

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29
Q

Field experiment

A

> Natural environment

> Independent variable manipulated (true experiment)

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30
Q

Strengths of field experiment

A

> high external validity - authentic behaviour

> better external validity - more realistic due to natural environment

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31
Q

Weakness of field experiment

A

> Ethical issues - invasion of privacy as no consent is given
difficult to support hypothesis due to extraneous variables (affects internal validity)

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32
Q

Natural experiment

A

> Natural or controlled setting

> independent variable is not manipulated - unplanned and has occurred because of a naturally occurring event

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33
Q

Strengths of natural experiment

A

Ethical as it doesn’t cause he event

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34
Q

Weakness of natural experiments

A

Not replicable because natural occurring event is rare

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35
Q

Quasi experiment

A

> Natural or controlled setting
independent variable not manipulated- based on existing difference between people eg. Age gender personality
planned manipulation of naturally occurring independent variable

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36
Q

Strengths of a Quasi experiment

A

Depends on laboratory or field experiment would have the streets of those experiments
Eg lab - high internal validity
Eg field - high external validity due to natural environment it’s more realistic

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37
Q

Weakness of a quasi experiment

A

> confounding variables could impact data

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38
Q

What are self report methods

A

Questionnaires and interviews

It is when participants report their own thoughts and feelings about a particular matter

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39
Q

Open questions

What data does it give

A

Participant can give any answer they wish

Qualitative data

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40
Q

Closed questions

What data does it give

A

There are a set number of responses which participants select from
Quantitative data

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41
Q

3 types of closed questions

A

Fixed choice option
Likert scale
Rating scales

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42
Q

Fixed choice option

A

Includes a list of possible options and respondents are required to indicate those that apply to them
eg. Age bracket

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43
Q

Likert scales

A

The respondent indicates their agreement with the statement using a scale from strongly agree to strongly disagree

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44
Q

Rating scales

A

Participants selected value that represents the strength of feeling about a particular topic e.g. 1 to 5

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45
Q

Strengths of questionnaires

A

> Close questions produce quantitative data which is easier to analyse
Open questions produce qualitative data which can provide unexpected answers and rich detail allowing researchers to gain new insights
Respondents may feel more able to reveal personal information in the questionnaire

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46
Q

Weaknesses of questionnaires

A

> Social desirability bias may cause respondents to deliberately answer in a way which is socially acceptable
Leading questions may cause respondents to answer in a particular way
Only certain types of people fill-in and return questionnaires therefore there may be a sample bias

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47
Q

What are interviewes

A

Mostly face-to-face questions though some may be conducted over the phone

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48
Q

Structured interviews

A

> Contain standardise preset questions
often a computer is used e.g. CAPI
Sometimes limited responses due to predetermined answers

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49
Q

Semistructured interviews

A

> Some preset questions
preset questions can be asked in any order
researcher can veer from preset questions
usually open ended

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50
Q

Unstructured interviews

A

> It is a conversation
Obtained very detailed data
Questions emerge during interview

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51
Q

Strengths of structured interviews

A

> Easy to analyse his answers are more predictable

> Can be easily repeated because the questions are standardised (more replicable)

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52
Q

Weakness of structured interviews

A

> The answers the participants give me be restricted by the question that is asked
Different questions may be interpreted in different ways by different participants

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53
Q

Strengths of unstructured interviews

A

> More detailed information can be obtained from each respondent
information can be accessed that might not be revealed by using predetermined questions

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54
Q

Weaknesses of unstructured interviews

A

> The interviewers own opinions may influence the interviewee this is interviewer bias
More difficult to analyse the data as there will be lots more of each respondent may have been asked different questions

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55
Q

Naturalistic observation

A

Research method carried out in a naturalistic setting in which the investigator does not interfere in any way just observes the behaviour in question

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56
Q

Controlled observation

A

Observation of behaviour under controlled conditions

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57
Q

Over observation

A

The participants are aware they are being observed

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58
Q

Covert observation

A

The participants are not aware that they are being observed

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59
Q

Structured observation

A

Researcher determines precisely what behaviours are to be observed and uses a standardised checklist to record the frequency in which they are observed within a specific time frame

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60
Q

Unstructured observation

A

The observer recalls all relevant behaviour but has no system

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61
Q

Participant observation

A

The researcher gets involved with the participant activity so they can experience it for themselves

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62
Q

Nonparticipant observation

A

The observer remain separate from the participants to maintain objectivity

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63
Q

Strengths of naturalistic observation

A

Truthfinding is due to no demand characteristics

Good external validity

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64
Q

Weaknesses of naturalistic observation

A

Poor internal validity due to no control

Small scale so one off

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65
Q

Strengths of controlled obervation

A

Good internal validity due to control of extraneous variables

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66
Q

Weakness of controlled observation

A

Introduces demand characteristics

Less generalisable to real life - lowers external (ecologically) valid

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67
Q

Strengths of overt observation

A

Informed consent - ethical

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68
Q

Weakness of overt observation

A

Hawthorne effect acting different due to knowing you’re being watched

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69
Q

Strengths of covert observations

A

Authentic behaviour

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70
Q

Weaknesses of covert observation

A

Unethical as there is no informed consent

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71
Q

Strengths of structured observation

A

Easily repeated - replicable

Good internal validity - standardisation

72
Q

Weaknesses of structured observations

A

Restrictive - may see other behaviours but won’t be able to use them because they are not on the checklist

73
Q

Strengths of Unstructured observations

A

Unrestrictive - record all behaviour including unexpected behaviours

74
Q

Weaknesses of unstructured observations

A

Harder to replicate as there is no standardisation

75
Q

Strengths of participant observations

A

High validity - better insights

76
Q

Weakness of participant observations

A

Less objective - going native - lose insight of what your doing
Hard to collect data

77
Q

Strengths of non participant observations

A

More objective

78
Q

Weaknesses of non participant observations

A

Thoughts and feelings lost

79
Q

When conducting and observation what may a psychologist use

A

Behavioural categories

80
Q

Behavioural categories

A

They are used in structured observations as a checklist

The target behaviour is broken down into behavioural categories and then operationalised

81
Q

3 sampling methods and which observations are they used in

A

Unstructured - continuous recording

Structured - event sampling and time sampling

82
Q

Continuous recording

A
  • all instances of target behaviour is recorded
83
Q

Event sampling

A

Counting the number of times in a particular behaviour occurs in q target individual or group doesn’t take account of the time just to tally

84
Q

Time sampling

A

Recording behaviour within a pre-established timeframe e.g. take note what a target individual is doing every 30 seconds of summer time interval

85
Q

Strengths of behavioural categories

A

Data collections is more structured and objective

86
Q

Weakness of behavioural categories

A

Categories are hard to define always exclusive and some overlap

87
Q

Strengths of events sampling

A

It is useful when target behaviour or event happens frequently as it could be missed in time sampling

88
Q

Weaknesses of the event sampling

A

Observer may overlook important details if the specified events is too complex

89
Q

Strength of time sampling

A

It is effective in reducing the number of observations that have to be made

90
Q

Weakness of times sampling

A

It may be on representative of the observation as a whole when behaviour is sampled

91
Q

What’s a correlation

A

When two things are measured in order to identify if there is a relationship between a single numerical values produced that is used to describe the relationship this is called a correlation co efficient

92
Q

Positive correlation

A

Both are those increase together

As one covariable increases so does the other covariable

93
Q

Negative correlation

A

As one covariable increases the other decreases

94
Q

No Correlation

A

No relationship between variables

95
Q

Curvilinear correlation

A

The relationship is predictive although it is not linear but curved

96
Q

Intervening variable

A

A verbal that comes between two other variables which is used to explain the associations between those two variables

97
Q

Continuous variable

A

Variable that can take on any value within a certain range

98
Q

What is the correlation coefficient

A

Number between zero and one
Tells us how strong the correlation is the nearest to one the stronger the correlation
It has a sign in front of the number which tells us whether the correlation is positive or negative

99
Q

What does the researcher do in correlations

A

Any correlation there is no manipulation of the two variables therefore it is not possible to determine cause and effect

100
Q

What are the three types of experimental design

A

Independent groups
matched participants
repeated measures

101
Q

Independent groups

A

Separate group of participants for each condition of the independent variable
E.g. independent variable music/new music equals one group has music playing in the other group has no music

102
Q

Matched participants

A

For a group of participants for each condition of the independent variable that they are fitted to certain characteristics
E.g. independent variable gender equal separate groups of males and females but will make sure the groups are matched for age or income

103
Q

Repeated measures

A

Every participant completes all conditions
E.g. one group has music playing in the same group does another test without music
Cannot be used if the independent variable is gender or age – (IV is quasi- pre-existing difference)

104
Q

Advantages of independent groups

A

> Order effects are avoided

> No demand characteristics

105
Q

Disadvantages of independent groups

A

> Individual differences may occur - the people in the groups are different people therefore there may be differences

106
Q

Advantages of repeated measures

A

> No individual differences

107
Q

Disadvantages of repeated measures

A

> Demand characteristics may appear

> Order effects

108
Q

Advantages of matched pairs

A

> Control for individual differences is better

> no order effects or demand characteristics as participants are only taking part in 1 condition

109
Q

Pilot studies

A

Used to test deign and test measures used
Can be used to test reliability (retest)
Used to identify extraneous variables
And to ensure all the ethical issues have been dealt with

110
Q

Ethics

A

The consideration of what is acceptable or right behaviour in the pursuit of a personal or scientific goal

111
Q

What is the 5 ethical issues

A
Informed consent 
Right to withdraw 
Deception 
Confidentiality 
Protection of participants
112
Q

Internal validity
What is it
What effects interval validity

A

Are we measuring what we set out to measure (accuracy)

Extraneous variables and confounding variables

113
Q

Extraneous variables

A

‘Nuisance’ variables that do not vary systematically with the iv and can often be controlled before the experiment begins

114
Q

Confounding variables

A

Variables that do vary systematically with the iv so we cannot be sure what caused the change in dv

115
Q

Participant variables

A

Any individual difference between people taking part that may interfere with the outcome of the investigation

116
Q

External validity

A

Can we generalise it
Population validity - is our sample representative
Ecological validity - is the environment accurate to real life
(Temporal)Validity over time - is it still accurate to today’s society

117
Q

What effects external validity

A

Demand characteristics

Investigator effects

118
Q

Demand characteristics

A

Participants may guess the aims of the research and then may act in a way they think is expected of them
Difficult to control

119
Q

Investigator effects

A

Unwanted influence of the researcher on the experiment

This may be unconscious behaviour such as smiling more with one condition than the other

120
Q

Situational variables

A

Any aspect of the experimental environment that may interfere with th outcome of the investigation

121
Q

Hawthorne effect

A

Added attention of being in a study affects participant behaviour

122
Q

Social desirability bias

A

When participants try to look good by answering/behaving in a socially acceptable way

123
Q

Interviewer bias

A

The interviewer affects the responses of the interviewee

124
Q

Greenspoon effect

A

When the interviewer makes affirmative noises eg mhhhmm

125
Q

Experimenter bias

A

When the experimenter effects the results eg through their body language, facial expressions etc

126
Q

Participant reactivity

A

Social desirability bias
Demand characteristics
Hawthorne effects

127
Q

Investigator effects

A

Experimenter bias
Interviewer bias
Greenspoon effect

128
Q

Randomisation (control for experimenter bias)

A

Using chance at every available opportunity

129
Q

Counterbalancing (control of order effects)

A

Half of the participants do one condition the other half does the other condition then they swap

130
Q

Single blind design (control for demand characteristics)

A

Use of deception to mislead participants

131
Q

Standardisation (control for experimenter bias)

A

Keeping everything the same for every participant

132
Q

Double blind design (control for demand characteristics and experimenter bias)

A

When both the researcher and the participant don’t know the aims of the study

133
Q

Reliability

A

Consistency
If they did the rest on another day would they get the same result
Is there standardisation of procedures and instructions

134
Q

Inter-rater reliability

A

Used in observation
Are the observers all scoring the same way
Testing for consistency

135
Q

Checking for reliability

A

Test, retest = reliability
Conduct the test again and see if you get the same result
Conduct a spearmans rho test comparing scores
Testing for correlation

136
Q

Improving reliability

A

Observers familiarise themselves with behavioural categories
Conduct a small scale pilot study
Compare the data observers have gotten by calculating a correlation co-efficient
Operationalise variables if needed
Repeat

137
Q

Purpose of peer review

A

> To validate the quality and relevance of research
To suggest amendments or improvements
Allocation of research funding

138
Q

Process of peer review

A

Validity
Significance
Originality
Method
Design
Report can be accepted, amendments suggest or rejected
Final reports submitted to panel and assessed for publication

139
Q

Evaluation strengths of peer review

A

Anonymity
Keeps a check on dishonest psychologists
Essential so that high quality researches produced

140
Q

Evaluation- weaknesses of peer review

A
Publication bias 
Burying ground-breaking research 
Expensive 
Time consuming 
Subjective 
Preserving status quo
141
Q

Qualitative data

A

Expressed in words, non numerical

142
Q

Quantitative data

A

Expressed numerically rather than in words

143
Q

Primary data

A

First hand from participants, collected specifically for the purpose of the research

144
Q

Secondary data

A

Data collected by someone other than the person doing the research

145
Q

Strengths of qualitative data

A

> Detailed so more realistic as it gives a better insight

> Greater external validity

146
Q

Weaknesses of qualitative

A

> Hard to analyse data as it is opinion based
Subjective to interpretation
Harder to spot patterns and trends
Research bias – if research has preconceptions about what they’re going to find

147
Q

Strengths of quantitative data

A

Simple to analyse measure of central tendency in
Objective in this open to bias
Easy to represent e.g. graphs

148
Q

Weaknesses of quantitative data

A

Narrow in scope information may fail to represent real life

May miss important information

149
Q

Strengths of primary data

A

Authentic as it is obtained from participants themselves

Target what you want to find

150
Q

Weaknesses of primary data

A

Time and effort consuming - requires planning and preparation resources

151
Q

Strengths of secondary data

A

Easier to use less time-consuming
Cheaper it’s already done
Peer reviewed = valid
Use data otherwise inaccessible

152
Q

Weaknesses of secondary data

A

Historically bias out of date
Subjective
Might not be valid in methodology

153
Q

What are measures of central tendency

A

They are descriptive statistics that find the average they can be the mean the mode or the median

154
Q

What is measures of dispersion

A

They find the spread/variety of the data
Range
Standard deviation – calculate how far scores deviate from the mean

155
Q

Streaks of the mean

A

Uses all of the dates are in the calculation so it’s more representative of the data as a whole

156
Q

Weaknesses of the mean

A

Is affected by extreme values

157
Q

Strengths of the mode

A

Can be used with qualitative data

Not affected by extreme values

158
Q

Weaknesses of the mode

A

Isn’t always in mind maybe more than one

Could measure that is a representative of the data as a whole

159
Q

Strengths of median.

A

Not affected by extreme values can be used when data is not interval

160
Q

Weaknesses of the median

A

Median may not even be in the data set if even amount of numbers
Isn’t representative

161
Q

Strengths of the range

A

Includes all data pieces

162
Q

Weaknesses of the range

A

Only takes into account the two most extreme values on representative of the day as a whole

163
Q

Strengths of standard deviation

A

All of the data is included in the calculation shows more representative of the data set

164
Q

Weaknesses of standard deviation

A

Affected by extreme values

It’s complicated and time-consuming

165
Q

Bar graph

A

Used for data in discrete categories
The bars are separated by a gap to show they are not continuous
It should plot the total or mean or percentage of scores for each group
The DV goes on the Y axes and the IV goes on the X axes

166
Q

Histogram

A

Used for continuous frequency data
The bars are touching to show its continuous
X axes is made up of equal size intervals of a single category the Y axis represents frequency
Sometimes the frequency polygon is drawn by joining the midpoint at the top of the bar

167
Q

Line graph

A

Used for continuous frequency data
X axis is made up of equal size intervals of a single category the Y axis represents frequency
Useful for comparing two sets of frequency data on the graph

168
Q

Scatter graph

A

Use for correlation or data
Co-variables go on the axis
The dots and what dreams are sometimes a line of best fit is drawn

169
Q

Normal distribution

A

Bell shaped curve
Mean mode and median all lie at the midpoint
No scores occur around during middle with fewer being plastered as they occur above and below the mean
The tiles of the curve never touch the horizontal axis as more extreme scores are always theoretically possible

170
Q

Positive distribution

A

Positive Skews is when longtail is on the positive side of the peak
No scores for below the mean
Mean mode and median I’m not in the same place – the main gates go to the right because it is affected by extreme values

171
Q

Negative distribution

A

And negative skews when the longtail was on the negative side of the peak
Most scores fall above the mean
The mean mode and median are not in the same place

172
Q

Inferential statistics

A

Draw conclusions about our data
Tell us whether our results are significant enough that we can generalise with any certainty
Based around probability – assess the probability that results could just be down to chance if there is a low probability of this then we can generalise

173
Q

Significance

A

If a test shows the results are significant we can accept our alternative hypothesis if they are not significant we accept that I’m null hypothesis
A test is significant if it meets the level of probability we have chosen
P< 0.05 or p< 0.01

174
Q

First 3 Stages of the sign test

A

> Record each pair of data working out the difference
Record a plus for a positive difference and the minus for a negative difference zero for no difference
Add up all the plasters and all the minuses and select the smaller value

175
Q

Second 3 stages of the sign test

A

The smaller value is the calculated value, S
Determine if it is a one-tailed or to two tailed test
State the hypothesis

176
Q

Last 3 stages of the sign test

A

Check the result is in the right direction
Find the critical value of S with a table of critical values
If the calculated value is equal to or less than the critical value the result is significant