1.
Research Methods
Activity Booklet (2)
Topics include:
Methods and Techniques
Investigation Design
Data Analysis and Presentation
Name:
2.
The Specification
The aim of this booklet is to provide you with practical activities to enhance your understanding of research
methods in psychology. Once completed it will provide a valuable revision tool…so take care of it!!
Methods and
techniques
Candidates will be expected to demonstrate knowledge and understanding of the following
research methods, their advantages and weaknesses:
Experimental method, including laboratory, field and natural experiments.
Studies using correlational analysis.
Observational techniques.
Self report techniques including questionnaire and interview.
Case studies.
Investigation
design
Candidates should be familiar with the following features of investigation design:
Aims.
Hypothesis, including directional and non-directional.
Experimental design (independent groups, repeated measures and matched pairs).
Design of naturalistic observations, including the development and use of behavioural
categories.
Design of questionnaires and interviews.
Operationalisation of variables, including independent and dependent variables.
Pilot studies.
Control of extraneous variables.
Reliability and validity.
Awareness of the British Psychological Society (BPS) Code of Ethics.
Selection of participants and sampling techniques, including random, opportunity and
volunteer sampling.
Demand characteristics and investigator effects.
Data analysis
and
presentation
Candidates should be familiar with the following features of data analysis, presentation and
interpretation:
Presentation and interpretation of quantitative data including graphs, scattergrams
and tables.
Analysis and interpretation of quantitative data. Measures of central tendency
including median, mean, mode. Measures of dispersion including ranges and
standard deviation.
Analysis and interpretation of correlational data. Positive and negative correlations
and the interpretation of correlation coefficients.
Presentation of qualitative data.
Processes involved in content analysis.
4.
Summarising Quantitative Data (in graphical form)
Graphs are a useful way of summarising data which enable psychologists to easily see
trends or patterns in data.
Three graphs which are commonly used to display quantitative data are:
Histograms
Bar Charts
Notes:
This graph is likely to be used when:
Notes:
This graph is likely to be used when:
5.
Scattergrams
Task: Fill in the gaps below!
1) The bars on a ____________ are joined together and are all of an identical
______________.
2) A histogram is commonly used to show __________ (e.g. IQ or test)
3) Bar charts are a useful way of showing ___________ statistics (e.g. percentages or
ratios)
4) Bars on a bar chart are not ___________ together because the scale is not
_______________.
5) Scattergrams are used to show the ____________ and _____________ of correlations.
6) Correlations can either be ______________, negative or have no correlation.
Analysis and interpretation of quantitative data:
Notes:
This graph is likely to be used when:
6.
Measures of central tendency tell the researcher where the average is in a set of data. The
three measures of central tendency you need to know well are the mean, median and
mode.
Complete the sentences below:
1. The _________ is known as the ___________ average. It is calculated by adding up
all the scores in a set of data and then ___________ them by the total ___________
of scores.
2. The _____________ is the middle value of a data set. It is calculated by putting the
data in _______ and finding the __________ score. If there is an ________ number
of scores, you should add the two middle scores together and __________ by ____.
3. The ___________ is the most ___________ occurring score. It is the easiest to
calculate – simply put your data in ________ and work out which one occurs the
__________!
Calculate the mean, median and mode for the following:
1a) Data from a psychology quiz:
1,2,3,7,10,20,30,43,47,48,50.
Mean = Median= Mode=
1b) The number of faces recalled out of 12 in a free recall task:
1,1,5,2,3,7,6,5,2,1,8,7,9,5,4,3,2,5.
Mean= Median= Mode=
1c) Scores on a questionnaire (out of 25).
20,30,25,16,13,14,25,26,28.
Mean= Median= Mode=
In addition to wanting to know the statistical average of the data, researchers occasionally want to
work out how much variability there is in a data set. This is known as a measure of dispersion.
One way of calculation the measure of dispersion within a data set is to calculate the range. This
incredibly easy method involves subtracting the lowest score from the highest score. That is it!
7.
What is the range for the following data sets?
a) 5,4,1,2,1,2,3,4,5,6,8,7,2.
b) 9, 11, 16, 4, 6, 17, 22, 35, 2, 12, 13.
c) 3, 4, 5, 8, 11, 14, 12, 16, 1, 9, 15, 17.
Standard Deviation
Standard deviation is the measure of the spread of scores around the mean (in other words, it tells
us how far the scores are scattered around the mean). It is the most powerful measure of dispersion
as it takes all scores into account. As a result, it is often used my researchers who want to know
more about the dispersion of their data. Below is an example of how a standard deviation might
look.
8.
Good News! You will not be asked to calculate a standard deviation in the exam. However,
you may be asked what the standard deviation tells you about a set of data and why it is
used.
If the standard deviation is ___________ it tells us that many of the data points are
far away from the mean.
If the standard deviation is small, it tells us that the data was __________ clustered
around the mean.
No standard deviation tells us that all data values were the same – and there was no
variation at all! This happens when all the data points are equal.
Exam Question – June 2011 (modified)
1) Two different drug therapies were tested on a group of patients. The table below
shows the improvement made between the start and end of the treatment. Explain
what these findings suggest about the different therapies.
Average Range Standard Deviation
Therapy A 6.5 2 - 19 5.9
Therapy B 6 4 - 9 7.8
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9.
Correlations
Non-experimental methods
All of the previous research methods we have looked at so far have been experimental.
This means that the researcher has at least one IV, one DV, and usually will manipulate
and control the experimental situation in some way to gain results. However, in
psychology, there are also non-experimental methods of investigation. This is where the
researcher investigates phenomena in a way where there is no manipulation of variables.
In non-experimental methods, the researcher uses various methods to measure
variables, and looks for relationships. The non-experimental methods you need to know
about are
Correlations
Interviews and questionnaires
Observations
Case Studies
Content analysis
What is a correlation?
A correlation is a relationship between two variables. A
correlational design is a way to test the relationship between
these variables. A participant provides data for both variables.
A correlational design allows us to test whether 2 or more
phenomena are related, and if so how strongly
In a correlational design, there are no independent or
dependant variables, but co-variables.
When do we use a correlational design?
To test a hypothesis about a relationship between two variables, for example:
__________________________________________________________________________
__________________________________________________________________________
__________________________________________________________________________
When looking for a relationship that would be unethical to manipulate for an
experiment, for example:
__________________________________________________________________________
__________________________________________________________________________
__________________________________________________________________________
How to use correlations
10.
Decide what co-variables you will be measuring, and operationalise your
variables.
Measure each participant on both co-variables.
Plot the values on the scatter graph to see if there is a relationship. Carry out a
statistical test to see if the relationship is significant or due to chance.
Correlation Coefficients
The correlation coefficient is measured from _______ to _______. A correlation can be
positive, negative or no correlation. The ________________ the number, the stronger the
relationship.
Match the descriptions
Type Description Coefficien
t
Example
Positive
Correlation
There is no relationship
between the variables
0 to +1 Shoe size and IQ
Negative
Correlation
As one variable
increases, the other
decreases
Close to 0 The taller a person is the
heavier they are
No
Correlation
As one variable
increases, the other
also increases
0 to -1 The more alcohol you
drink, the less can
remember
11.
Task:
What correlation would you expect to find in the following situations?
A. Hand-span and height:
____________________________________________________________________
B. Smoking and life expectancy:
____________________________________________________________________
C. No. of pets owned and cleanliness of home:
____________________________________________________________________
D. No. of Facebook friends and avg. units of alcohol drunk:
____________________________________________________________________
E. No. of A levels taken and levels of stress:
__________________________________________________________________
F. Size of DVD collection and money in bank account:
__________________________________________________________________
Correlation and Causation
You have performed a statistical test, and found that two co-variables are correlated
(there is a relationship). What does this tell us about cause? When looking at correlation,
it is important to remember that:
Just because there is a relationship, we cannot be certain that one co-variable caused the
other. If we find that there is a relationship between co-variables X and Y, there are three
possible explanations:
1. X caused Y
2. Y caused X
3. A third variable (Z) caused the change to both X and Y
This third variable is known as an intervening variable.
Example 1:
It has been established that there is a strong positive correlation
between ice cream sales (X) and shark attacks (Y); the more ice cream
12.
that is sold, the more shark attacks there are. Three possible explanations:
1. The sale of ice cream causes shark attacks to increase
2. The shark attacks cause the sales of ice cream to increase
3. __________________________________________________________________
__________________________________________________________________
___________________________________________________________________
Which explanation seems the most plausible?
Example 2:
There is a positive correlation between the number of hours a child
plays violent computer games for (X), and the level of aggression
that child shows (Y).
1. ____________________________________________________________________
____________________________________________________________________
____________________________________________________________________
2. ____________________________________________________________________
____________________________________________________________________
____________________________________________________________________
3. ____________________________________________________________________
____________________________________________________________________
____________________________________________________________________
Evaluation of correlational research
Precise information on the degree of relationship between variables is available in
the form of the correlation coefficient. If a significant relationship is found, it can
suggest ideas for experimental studies to determine cause and effect
relationships.
Can be used when it would be impractical or unethical to manipulate variables.
It can make use of existingdata, and so often can be a quick and easy way to carry
out research.
13.
Often, little manipulation of behaviour is required; all the researcher does is
measure existing variables. Therefore, it is often high in mundane
realism/ecological validity.
No causeandeffectrelationships can be inferred. E.g. one variable cannot be said
to cause an increase or decrease in the other variable. The relationship could be
explained by a third intervening variable. As such, correlations are open to
misinterpretation.
As with experiments, the correlations may lack internal/externalvalidity. For
example the method used for measure IQ might lack validity, or the sample may
lack generalisability.
Correlations should be plotted out on scatter graphs to properly illustrate the
relationships between two variables. A correlation co-efficient of zero may not
form a random pattern (see below).
The graph here shows the relationship between
arousal (stress) and performance on a task. When
arousal is too high or too low, performance is
impeded. This is known as the Yerkes-Dodson effect.
14.
Correlational Analysis:
Correlations are designed to investigate the strengthand direction of a relationship
between two variables. The strength of this correlation is expressed by the correlation
coefficient. The correlation coefficient is always between +1 and -1 where +1 represents a
perfect positive correlation and -1 represents a perfect negative correlation.A correlation
coefficient of 0 means that there is no correlation between the two variables.
15.
A researcher wanted to find out the relationship between the number of hours a child spent
in day care and their level of aggression. Plot the following data at the bottom of the page.
Does the scattergram show a negative or positive correlation? What does this mean?
Participant Number of hours in
day care per week
Score on
aggression scale
(out of 50)
1 30 45
2 35 48
3 10 12
4 35 40
5 30 28
6 6 6
7 8 10
8 15 20
9 40 48
10 20 25
16.
Presenting and Analysing Qualitative Data:
Due to its richness and non-numerical nature, qualitative data cannot be analysed or
displayed by the methods we have examined so far. Instead, this data has to be
analysed using a process called content analysis.
Traditional forms of content analysis are conducted through six stages. Summarise
these in the chart below.
The main problem with any form of content analysis is that it can be
interpreteddifferently by different researchers. Taking the original data out of
context may lead to it being misinterpreted or a different slant being taken. The only
way to control for this is through the use of an external party who analyse, interpret and
justify every decision they make during the process. Alternatively, several researchers
can work together at each step.
17.
End of section assessment questions:
1) What is the difference between a histogram and a bar chart?
2) Which type of data can be displayed in both graphs and tables?
3) When would you be likely to use the mode as a measure of central
tendency?
4) What does a large standard deviation suggest about the data?
5) Circle the correlation co-efficient which can be described as a strong
positive correlation.
+0.06 +0.66 +0.99
6) Correlational studies show a link between two variables but they do not
show…?
7) List the six stages involved in a traditional content analysis.
8) What is one problem that might occur when conducting a content analysis
and how can it be controlled?
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