Reaserch Methods Flashcards
1
Q
What are strengths of a questionnaire
A
Time/cost effective
Lots of data easily/quickly
Closed questions are easy to analyse
2
Q
Weakness of a questionnaire
A
Demand characteristics(social desirability)
Response bias accequense bias
3
Q
What are the 3 types of interviews
A
Structured
unstructured
Semi - structured
4
Q
Strengths of interviews
A
Rich data (through open questions)
Less demand characteristics
5
Q
Weakness of an interview
A
Not cost effective
Time/effort/training involved
Harder to analyse (if open question)
6
Q
What is an open question
A
A question which allows responders to write there own answers
Qualitative data
7
Q
What is a closed question
A
Set number of responses
Quantitative data
8
Q
What shouldn’t be in a questionnaire
A
Dont ask personal details
Dont use leading questions
Dont ask double barrel questions
Avoid ambiguity/jogan
9
Q
What are behavioural categories
A
Dividing target behaviour (aggression) into a specific subset of operationalised behaviours
It allows us to research to gather valid and reliable data
Carrying out an observation without the use of these would not be clever
10
Q
What is time sampling
A
Recording behaviour in a given time period
11
Q
What is a strength of time sampling
A
Reduces number of observations needed
12
Q
What is a weakness of time sampling
A
May not be a representation of whole behaviour
13
Q
Definition of event sampling
A
Counting the number if retimes a certain behaviour occurs
14
Q
Strengths of event sampling
A
Useful for infrequent behaviour
15
Q
Weakness of event sampling
A
May miss out on events
Takes a lot of time
16
Q
What is a covert observation
A
PPs are recorded without there knowledge or consent
17
Q
Strengths of a covert observation
A
No chance of demand characteristics
18
Q
Weakness of a covert observation
A
Ethical issues
19
Q
What is an overt observation
A
PPs are recorded with there knowledge and consent
20
Q
What is a weakness of a overt observation
A
Chance of demand characteristics
21
Q
Strengths of an overt observation
A
No ethical issues
22
Q
What is a non participating observation
A
Based on observations made from a distance or from outside the group or situation being studied
23
Q
Strengths of a non participating observation
A
No investigator effect
24
Q
A weakness of non participating observation
A
Less insight
25
What is a participant observation
Requires the researcher to actually join the group or take in the situation they studying
26
A strength of participant observation
Greater insight
27
A weakness of participant observation
Possible investigator effect
28
What is an unstructured observation
Makes nites on behaviour soon
Produces qualitative data
29
What Is a structured observation
A researcher determines precisely what behaviours are to be observed ( behaviourist categories)
Uses a check list
Quantitative data
30
What is a controlled observation
Watching + recording behaviour where research tries to control certain variables
31
A strength of a controlled observation
High internal validity
High internal validity
32
A weakness of a controlled observation
Low ecological validity
Chance of demand characteristics
33
What’s a naturalistic observation
Watching + recording naturally occurring behaviour
34
Strengths of a naturalistic observation
High ecological validity
Low demand characteristics
35
Weakness of a naturalistic observation
Low internal reliability
Low internal validity
36
What is matched pairs
Experimental design where PPs are closely matched with another PP
37
What is a strength of matched pairs
No order effect
Control of participant variables
38
A weakness of matched pairs
Finding pairs of PPs can be hard and time consuming
Large number of people need to find the best matched pairs
39
Definition of a independent group
The PPs are exposed to one of the conditions
40
A strength of independent groups
No order effect because condition is only done once by the participant
Lower demand characteristics - because the person doing the test doesn’t know what variable is being manipulated
41
Weakness of independent groups
More PPs needed
No control over participants variables
42
What is a repeated measured design
Experimental design where PPs are exposed to both condition
43
A strength of repeated measure design
Less PPs needed
No participant variables - no individual differences between PPs is different conditions
44
Weakness of repeated measure design
Risk of order effect - makes test less accurate because they know what’s is going on
Demand characteristics - person may try act differently to try help researcher
45
What is a quasi experiment
Variable being tested cannot be changed IQ
Cannot be manipulate variables
Independently variable exists
46
What is a natural experiment
Research takes advantage of naturally occurring variables
47
Strengths of a natural experiment
High ecological validity - real life setting
Can study things it would be inappropriate to study or manipulate variables usually
Low demand characteristic’s - because it is done in a natural occurring environment
48
Weakness of a natural experiment
Low internal validity - less control over variables
Low internal reliability - very hard to repeat exactly
No random allocation of PPs conditions
49
What is a field experiment
A experiment that takes place in a natural environment but the independent variable is still manipulated
50
Strengths of a field experiment
High ecological validity - real life setting
Low demand characteristics - real life setting
51
Weakness of a felid experiment
Low internal validity - don’t have control over i.v
Low internal reliability - hard to repeated
52
What is a laboratory experiment
A experiment that is carried out in a controlled environment where the independent variable is manipulated
53
Strengths of a laboratory experiment
High internal validity - control over variables
High internal reliability - means the experiment can be repeated and is consistent
54
Weakness of a laboratory experiment
Low ecological validity - artificial setting
Chance of demand characteristics - participant changes behaviour due to knowing it is a test
Investigator effect - a researcher could unintentionally or unconsciously influence the outcome of the research they are conducting
55
Who was the person in the case study
Genie
56
What are findings of this case study
Supports critical period
Nurture rather then nature
57
Strengths of a case study
Ecological validity
Low demand characteristics
Rich data (qualitative detailed)
Unique cases
58
Weakness of a case study
Low internal validity/ reliability
Idiographic in nature - can’t generalise
Possible investigator effect
Ethical issues:
Informed consent
Psychological stress
59
How do we set up content analyse
Qualitative data is collected from a diary or interview
Coding units are created
Data is tallied to see how often each coding unit occurs
This qualitative data can therefore be statistically analysed
60
Definition of a coding unit
Predetermined discrete categories (must be fully operationalised)
61
Strengths of content analysis
Fewer ethical issues - no permission needed
Involves both qualitative data and quantitive data
62
Weakness of content analysis
Limited insight - studied indirectly
Possible observer bias (investigator effect) - less objective
63
What is thematic analysis
A qualitative approach
Involves identify recurring themes
64
What is a independent variable
The variable directly manipulated by the researcher (the cause)
65
What is a dependent variable
The variable you think is affected by changes in the independent variable (the effect)
66
What’s an extraneous variable
Any variable that could affect the dependent variable ( other than i.v)
67
What are the types of extraneous variables
Participants:
Connected with the individuals
Situation:
Connected with situations
68
What are confounding variables
If these variables change systematically within the i.v
69
What is an aim
A general statement about the purpose of the study
70
What is a hypothesis
A precise testable statement inducting the expected outcome of investigation
71
What is a directional hypothesis
A directional hypothesis states which direction the result will go in
This is also known as a one tailed hypothesis
This is used when there has been prior research
72
What is a non directional hypothesis
A non directional hypothesis doesn’t state the direction
This also known as a two tailed hypothesis
This is used when there hasn’t been prior research
73
If there has been previous research on a topic what type of hypothesis is it
Yes - directional
No- non-directional
74
How to know weather a directional or non directional hypothesis is asking for a difference or relationship
If it is a difference there will be conditions
Non-directional = there will be a difference in
Directional = PPs who __ will____(higher/lower/better/worse) than PPs who ___
If it is a relationship the same PPs are being measured doing two things
Non directional = there will be a correlation
Directional = there will be a positive/negative correlation between
75
What’s the most important thing to do with variables
Operationalise them
What each group is doing (i.v)
How their behaviour is being measured (d.v)(units)
76
How do we chose which sampling technique to use
First we must identify the group of people we are interested in studying (target population)
This would be fairly large so we select a sample
Sample ,use be representative of the target population and not biased
If it is then it has population validity
77
What is opportunity sampling(connivance sampling)
Researcher selects anyone who is available to take part in
Connivance sampling
78
What is volunteer sampling (self selected sampling)
PPs select themselves
79
What don’t volunteer sampling and opportunity sampling have
Population validity
80
What is random sampling
Every person or item in a given target population has an equal chance of being selected
81
What is systematic sampling
Every nth person
82
What is sampling bias
Sampling bias can occur when some members of the target population are more likely to be chosen
83
What are the 3 ways sampling bias occurs
Through sampling techniques
Through choice Of population
Through sample size
84
Why can sampling techniques cause sampling bias
Because there will always be an element of self selection
85
Why does choice of population have a high chance of sampling bias
This can occur in relation of target population if certain populations are targeted
86
What can a sample size cause sampling bias
Can occurs in relation to sample size
Small sample more prone to bias
More likely to find characteristics unlike the majority
87
Why and how is stratified sampling
It is used in conjunction with random sampling
To over come sample bias stratification is used
88
What conditions must be met so stratified sampling can occur
Specify characteristics of the sub groups in advance
Then selecting from each group in same proportion that appear in target population
89
What is informed consent
A participant must be fully informed of aims and producers of the study should be made clear along with right to withdraw
90
How to deal with the ethical issue of informed consent
A consent letter or form detailing all relevant information
That may effect their decision to participate if agreed participants sign
If the child is under 16 then parental signature is required
91
What is deception
Were information must not be withheld from participants nor should they be mislead
If they are likely to object when debriefing at the end of the producer
92
How to deal with deception
Full debriefing and be made aware of the true aims of the investigation
Any information not supplied with during the study
existences of other groups or experimental conditions
93
What is protection from harm
Participants have to be protected from physical and mental harm
Including under stress
Risk of harm must be no greater than everyday Life
94
What are some of the ways to deal with protection from harm
PPs should be told what is happening with there data and given the right to withdraw and right to withhold data
This is important if retrospective consent is a feature of the study
Should be reassured that their behaviour was typical or normal
Extreme cases the participant may require counselling which the researcher should provide
95
What is the data protection act
It requires us to maintain the confidentiality of people who we have collected data from
If we don’t have consent
Participants should not be observed in situations where they would not normally be expect others to observe them
96
How to deal with ethical issue of data protection
If personal details are held they must be protected
They should maintain anonymity usually refer to participants as numbers or initials
when writing up a case study they are referencing to by initial or number
97
How can we avoid most ethical issues
By gaining informed consent from potential PPs by using an information sheet/consent form
98
What should we do on a information sheet
Explain the objectives of the study and what it will involve
Disclose anything that might influence PPs willingness to take part in study
Give PPs the opportunity to ask questions the researcher about the study
Stress the fact they can withdraw at any time
Guarantee state that data will be confidential
99
What should be on a consent form
Be signed by pp when they have read and understood the information sheet and have opportunity to ask questions
Be signed by pp (parent if under 16)
Be written clear and understandable way
100
What is presumptive consent
Taking a random sample of the production and introducing them to research
Including any deception
See if they would give their consent
101
What is prior general consent
PPs are misinformed but only those who agree that such practice is acceptable are selected
102
What is retrospective informed consent
Following the study PPs have right to withdraw results
103
What is reliability
Reliability refers to how consistent a measuring device is
It is measured using a correlational analysis
The correlation coefficient should exceed +80 for reliability
104
What is test-retest reliability
Same PPs complete same test
Uses a test of correlation between two sets of scores
High correlation coefficient incentives high reliability
105
What is inter research
Assessing in extent to which different researchers agree with each other
106
What is intra research
Assessing by extent to which the same researcher agrees with themselves
107
How do we improve reliability
More than one measurement from each participant
Training researchers
Make sure research gets are looking for the same thing when more than one
Use pilot studies
108
What is a pilot study
A small scale sturdy conducted on a small sample
It helps researchers to identify any major problems chosen method design + instructions given to participants and so on
Check items on questions to make sure they are easier to answer and unambiguous
109
What are the features of a science
Objective
Replicability
Falsifiability
110
What does something being objective mean
Not based on opinion prejudice or emotion
111
What does something having replicability mean
Ability for procedures/findings to be repeated
112
What does something having falsifiability
Ability for a theory to be proven false
113
What is a paradigms
A shared set of assumptions about the subject matter of a disciplines + the method used to study it
114
What are the 3 types of science
Pre science
Normal science
Revolutionary science
115
What is pre science
No accepted paradigm
116
What is a normal science
General accepted paradigms
117
What is a revolutionary science
When there is a paradigm shift
118
What is peer review
The scrutiny of research by independent experts ( who work in the same field) before publication
Asses the research ( in terms of validity significance and originality) recommend wether they think its suitable for publishing or not
Editor of the journal makes the decision wether to accept (publish) or reject the research
It acts as a system of quality control + ensures that published work is high quality and relevance
It is used to evaluate proposed designs for research funding
119
What are problems with peer review
May be biased (anonymity of reviewer)
Publication bias negative findings often ignored
Tends to be conservative (savouring their own theory)
120
How can psychology help the economy
Role of the farther
Treatments for mental disorders
121
How is the role of the farther help use psychology for the economy
Childcare is seen as the mothers responsibility + only hers while the farther is free to carry out his ‘natural’ role as provider for the family
The farther may fulfil a qualitatively different role to the mother
This role is no less valuable in child’s upbringing
Both Parents are equally capable of providing the emotional support necessary for healthy psychological development
This can promote flexible working arrangements within the family
Now the norm is that the house hold the mother is a highe earner + works longer hours
Many couples share responsibilities during the working week
This means that modern parents are better equipped to maximise their income and contribute more effectively to the economy
122
What is an abstract
First section in a journal
Short summary abstracts (150-300) words
Includes major elements
123
What are major key elements in a abstract
Aims + hypothesis
Method/producers
Results and conclusions
124
What does a scientist do with a group of abstracts
Reads a lot of them to try and identify the studies that are worth further examination
125
What is a introduction
A literature review of general area of research detailing relevant theories
Concepts and studies are related to the current study
Follow a logical progression
126
What should an introduction do
Beginning broadly
Gradually becoming more specific
Until aims + hypothesis is presented
127
What is in amethod in a scientific report
Design
Sample
Apparatus/material
Procedure
Ethics
128
What is the design
Should clearly state (groups/observation) why the type has been used
129
What is in the sample in the method
Information related to who was involved in the study
How many there were
Biological/demographic
(As long as it keeps anoynimity)
Method + target population
130
What is apparatus and material in scientific report methods
Detail of any assessments instruments used
Other relevant materials
131
What is a procedure
A recipe style
Everything that happened in the investigation from beginning to end
Keep a record of everything said to PPS
Standardised + debriefing
132
What is ethics in the method
An explanation of how these were addressed during study
133
What. Are the results in a scientific report
Summary of the findings in an investigation
Features some descriptive statistics
134
What are the types of statistics used in results of a science report
Inferential statistics
135
What is an inferential statistic
Reference to choice of statistical test calculate
Critical values
Level of significance
Final outcome
136
What’s happens to raw data collected in science report
Calculations appear in a appendix rather than the main body of the report
If a researcher uses qualitative methods of research results/findings will have to be analysed with themes or categories
137
What does the discussion in a scientific report mean
Summaries findings/results
Verbalise them instead of statistically
Talked about in context of evidence presented in introduction
Other researchers may consider relevant
Limitations of the present investigation
And how they can be addressed in future studies
Wider implications of the research is considered
Real world application what they have discovered
What contributions the investigation have made to existing knowledge
Base within the field
138
What is in a reference in a scientific report
Includes all details of source material cited in report
Journal formate
139
What should a journal format follow
Author(S)
Date article title
Journal name (italics)
Volume(issues)
Page numbers
140
Why do we present data and how we interpret data into quantities
Data is collected as a result of research it is important that researchers presents their findings in an accessible way
One of the most basic ways to do this is to present a summary of the data in a table
Graphs are a use of way of summarising data which enable psychologists to easily see trends or patterns in data
141
How should a histogram be drawn
All intervals are shown
All equal width
Columns touch each other
142
When do we use a histogram
When we have continuous data
143
How do you draw a bar chart
Columns are equal width
Columns Don’t touch each other
Only interval we are interested in are shown
144
When do we use a bar chart
When we have non continuous data
145
What is a scattergram
Each piece of data contributes one point on scattergram
Resulting indicate type + strength of relationship points are plotted not joined
146
What is an advantage of using correlation analysis
Establish relationship between variables
Researchers to analyse situation that could not be manipulated experimentally for ethical/practical research
147
What’s a disadvantage or correlation analysis
Cannot establish cause + effect
Misinterpretations
Presuming constant
148
What is measure of central tendency and how is it used
It tells researchers where the average is in the set of data
Mean median + mode
149
What is the mean
It is known as the arithmetic average
It is calculated by adding up all the scores in a set of data + then divide them by total value of scores
150
What is the measure of central tendency that takes into account adding up all the values and dividing by the amount of values there
Mean
151
What is the advantage of using the mean
Most representative as takes all scores in to account
152
What is a disadvantage of using the mean
It can be distorted by extreme values
153
What is the median
The middle value of a data set
It is calculated by putting the data in order + finding the middle score
If there is an even number of scores you should add the two middle scores together and divide by 2
154
What do you do with the median if you have an even number of scores
If there is an even number of scores you should Add the two scores and divide them by 2
155
What is an advantage of using the median
It is unaffected by outlying values
156
What measure of central tendency takes into account the middle value of a data set
Median
157
What is a disadvantage of using the median
Only takes one or two scores into account so not good with small sets of data
158
What is the mode
The mode is the most frequently occurring score
It is the easiest to calculate - simply put our data in order + work out which one occurs the most
159
What is the measure of central tendency that takes into account the most frequent occurring score
Mode
160
What is an advantage of using the mode
Unaffected by outlying values
161
What is a disadvantage of using the mode
Can be unrepresentative if most frequent is at the end of set data
162
What is a measure of dispersion
We want to work out how much variability there is in a data set
This is a measure of dispersion
163
What are the two measures of dispersion
Range and standard deviation
164
What is the range and how do we calculate it
How spread out the data is
Subtracting the smallest score from the largest score
165
What is an advantage of using the range
It is easy to find and use
166
What is a disadvantage of using the range
Is it completely ignores middle values so can be misleading
167
What is standard deviation
The measure of spreads of scores around the mean
( how far the scores attach around the mean )
168
What is an advantage of using standard deviation
Is that it is the most powerfully measure of dispersion as it takes all scores into account
169
What is a disadvantage of using standard deviation
It is not quick + easy to calculate
170
What does it mean if standard deviation is large
If standard deviation is large it tells us that many of the data points are far away from the mean
171
What does it mean if standard deviation is small
If standard deviation is small it tells us that the data was closely clustered around mean
172
What does it mean if there is no standard deviation and when does it occur
If there is no standard deviation tells us that all data values were the same
There was no variation at all
When all data points are equal
173
What are the types of data
Quantitative
Qualitative
Primary
Secondary
174
What is quantative data
Data expressed using numbers
175
What is a strength of quantitive data
Easy to analyse
176
What is a weakness of quantitive data
May oversimplify reality
177
What is qualitiave data
Data that is expressed in non-numerical ways
178
What is a strength of qualitative data
Provides detailed information
179
What is a weakness of qualitative data
More difficult to analyse
180
What is primary data
Data that is obtained first hand
181
What is a strength of primary data
Researcher ha control over the data they get
182
A weakness of primary data
Lengthy/expensive process
183
What is secondary data
Data that has been collected by a researcher that someone else who has previously obtained that data
184
What is a strength of secondary data
Simpler/cheaper process
185
A weakness of secondary data
Data may not fit the needs of the study exactly
186
What is data distribution
When we plot data and we can see an overall pattern Normal
187
What is a normal distribution
A classic bell-shaped curve
In normal distribution the mean median + mode are all exact mid-point
188
What are the types of skewed distribution
Negative
Positive
189
What makes a distribution negatively skewed
Mode>mean
190
What type of distribution is it if the mode > mean
Negative
191
Example of negative skewed distribution
If an exam is easy most people will score high
192
Why do we end up with skewed data
Populations scores are not distributed equally around the mean
193
What makes a distribution positively skewed
Mode < mean
194
An example of positive skewed data
Plotting a distribution for depression
0-50 being normal and 50+ clinically depressed
195
Why do psychologists analyse there results
They are interested in how likely it was that their results were due to chance
196
How do researchers check if there results are meaningful or significant
They judge it as significant or not b carrying out an inferential test on the data that has been gathered
197
What type of test would a researcher use to compare significance
A test that compared sample means and apply rules of probability and statistical significance
198
How is probability expressed
Probability or p in science is expressed as a number between 0 and 1
199
What does 0 mean in a probability
Means event defiantly won’t happen
200
What does 1 mean in probability
Means an event will definitely happen
201
What is the equation to calculate probability
Probability = number of particular outcomes/number of possible outcomes
202
How can probability be expressed
As number or percentage
0.5=50%
203
Why is level of significance used
To know weather to accept or reject a hypothesis
204
What does a statistical test find
A statistical test is to find out how likely it is that we have found in our sample actually reflect what happens in the population
205
What is a statistical test used for
Statistical tests are used to test the probability that the null hypothesis is true
206
What causes a null hypothesis to be accepted or rejected
If the probability of the null hypotheses being correct is lower than the level than level of significance it can be rejected
207
How is level of significance expressed
A probability value between 0-1
208
What does the probability value indicate
The probability of the null hypothesis being true
209
What kind of number would Researcher want and why for level of significance
A very small value in order to be able to claim the results are stay significant
210
How can level of significance be shown
Decimals
Percentages
5% p=0.05
1% p=0.01
211
What is the generally accepted level of significance
5% p=0.05
212
What is a more stringent level of significance
P=0.01
213
Why would psychologists use a stringent level of significance
When they Need to be more sure of the results
214
What makes a value significant and what happens to the hypothesis
Anything less than the level of significance it is significant and it is unlikely that the null hypothesis is true
215
What happens if the probability is less than the level of significance
We reject the null hypothesis and accept the alternative hypothesis
216
What don test statistics indicate
What is true in the real world
217
What can effect the null hypothesis
There is a possibility that errors will be made when deciding what to do with the null hypothesis
218
What are the two types of errors in level of significance
Type 1
Type 2
219
When does a type 1 error occur
When a null hypothesis is rejected when it should have been accepted
220
What is a type 1 error known as
A false positive
221
What happens when there is a type 1 error
We accept alternative hypothesis (a variable had an effect on another or there was a relationship between two variables)
If there is no such effect or relationship we have made a type one error
222
How do you find the likely hood of making a type 1 error
The likely hood of making a type 1 error is equal to the level of significance employed
With a level of p=0.0s or 5% it is 1 in 20 (5%)
223
What is a type 1 error referred to
An error of optimism
224
What is an error of optimism
When you claim to have found a relationship/effect but are wrong because its not actually there
225
When does a type 2 error happen
Occurs when a null hypothesis is accepted when i should have been rejected
226
What happens when a type 2 error occurs
We reject the alternative hypothesis and suggest there is no effect of a variable or relationship between variables
If there is an effect or relationship we have made a type w error
227
What is a type 2 error also known as
A false negative error
228
What is a type 2 error referred to as
An error of pessimism
229
What is an error of pessimism
You say you do not have an effect/relationship but are wrong because there actually is
230
What kind of number would a researcher want
They would want a very small value in order to be able to claim the results are or stay significant
231
How can probability be shown
As a decimal or percentage
5% =0.05
1%=0.01
232
What is a generallly accepted level of significance
5% (P=0.05)
233
What is a more stringent level of significance
P=0.01 or 1%
234
Why would a psychologist use a more stringent level of significance
A psychologist need to be more sure of the results
235
What makes something significant and what effect does this have of the hypothesis
Anything less than the level of significance is described as significant meaning it is unlikely that the null hypothesis is true
236
If the level of signifance is lower what can we do to the null hypothesis
We can reject the null hypothesis (alternative hypothesis can be accepted
237
What does a test statistic do
Gives indications of what is true in the real world
238
What can effect deciding the null hypothesis
There is still a possibility that errors will be made when deciding to do a null hypothesis
239
What is a type 1 error
A false positive error
240
When does a type 1 error happen
Occurs when a null hypothesis is rejected when it should have ben accepted
241
What does type 1 error mean we have done
We accept the alternative hypothesis (a variable had an effect on another or there was a relationship between two variables)
There is no such effect or relationship we have made a type one error
242
What are the chances of making a type 1 error
It is equal to the level of significance employed
If level of significance is p=0.05 or 5% it is 1 in 20(5%)
243
What is a type 2 error
A false negative error
244
When does a the 2 error happen
Occurs when a null hypothesis is accepted when it should have been rejected
245
What have we done if there is a type 2 error
We reject the alternative hypothesis and suggest there is no effect of a variable or relationship between variables
If there is an effect or relationship we have made a type 2 error
246
What is a type 1 error (optimism error)
Claim to have found a relationship but are wrong because it’s not actually there
247
What is a type 2 error ( pessimism error)
You say you do not have an effect/relationship but are wrong because there actually is
248
What are the 3 factors that effect which statistical test we use
Level of measurement
Research aims to
Experimental design
249
What are the 3 levels of measurement
Nominal
Ordinal
Interval
250
What is nominal data
Data that comes from recording the number of scores which fall into different categories (improving of not after treatment)
251
What is ordinal data
Data that is a number but only tells you about an order without having a fixed scale (e.g score of personal test)
252
What is interval data
Data that is a number with a scale where each unit on the scale is the same size (e.g time taken to complete task)
253
How do you know if a statistical test is looking for a relationship
If your study was a correlation the You will be investigating a relationship between variables
254
How do you know if a statistical test is looking for a difference
If your study is an experiment then you will be investigating a difference between two groups
255
How do you know if your experimental is using related groups
They use repeated measures or matched pairs
256
When do you use the sign test
When you have nominal data
When looking for a difference
When looking at related data
257
258
How do you do a sign test
State the hypothesis
Record data
Find calculated values
What type of hypothesis
259
What do you do when you state your hypothesis
One(directional) or two(non-directional) tailed
260
How do you record data in a sign test
Record each pair of data using (+) or (-) (0) if neither
261
How do you calculate values in a sign test
S is calculated by adding up the pluses (frequency) and adding up the minuses (frequency)
Selecting the smallest value
How Many PPs (ignore any zero values)
N = number of scores ignoring 0
262
What does S mean
Symbol for the test statistic we are calculating
263
What are the types of hypothesis in a sign test
One or two tailed
264
What type of significance do you use unless stated otherwise
Level of significance (0.05 if not stated otherwise)
265
What do you do if the investigation is looking for a difference
You think What type of design being used
266
What are the two types of designs used in statistical testing
Independent groups
Repeated measures
267
What statistical test do you use if you have nominal data and your investigating relationship
Chi-squared
268
When do you use a chi-squared
When there is nominal data and your investigating a relationship also when you have a difference and are using independent group
269
What statistical test do you use when you have nominal data and investigate a difference with independent groups
Chi-squared
270
When do you use a superman’s Rho
When you have ordinal data and are looking for a relationship
271
What statistical tests do you use when you have ordinal data and looking for a difference
Mann-Whitney
Wilcoxon
272
What statistical test do you use when you are looking for a difference and have ordinal data and independent groups
Mann-Whitney
273
What statistical test do you use when you have ordinal data and are investigating a difference and use a repeated measure
Wilcoxon
274
What statistical test do you use when you have interval data and a investigating a relationship
Persons R
275
What statistical test do you use if you have interval data and your investigating a difference
Unrelated T
Related T
276
What statistical test do you use when you have interval data and investigating a difference and independent groups
Unrelated T
277
What statistical test do you use when you have interval data and are investigating a difference and use repeated measures
Related T
278
What statistical test do you use when you have nominal data are looking for a difference and use repeated measure
Sign test
279
280
When do you use a sign test
When you have nominal data looking for a difference and use a repeated measure design
281
When do you use a Wilcoxon
When you have ordinal data are looking for a dirt fence and are using repeated measure designs
282
When do you use a Mann-Whitney
When you have ordinal data are looking for a difference and use indecent groups
283
When do you use Pearson R
When you have interval data and are looking for a relationship
284
When do you use a unrelated R
When you have interval data there is a difference and you use independent gouts
285
When do you use a related R
When you have interval data are looking for a difference and use repeated measures
286
What test are nominal
Chi-squared
Sign test
287
What tests are ordinal
Mann-Witney
Wilcoxon
Spearman’s Rho
288
What tests are interval
Unrelated T
Related T
Persons R
289
What test are in independent groups and a difference
Chi-squared
Mann-Whitney
Unrelated T
290
What test in repeated measures and difference
Sign test
Wilcoxon
Related T
291
What test are in relationship
Chi-squared
Spearman’s RHO
Persons R
292
What questions do you ask when picking a statistical test
What type of data are your using
What are you investigating
What type of design is being used
293
When do you use degrees of freedom and what are they used for
In order to interpret the results of some tests
Have to workout degrees of freedom
294
How do you calculate degrees of freedom
(Df) = (r-1) x (c-1)
295
What do r and c stand for in degrees for freedom
R = numbers of rows
C = number of columns
