Download 1.2-Methods-Self

1.2 Methods
SELF REPORTING DATA
Why do we carry out
psychological research?

Where do we begin?

Aim

Hypothesis - prediction about what is likely to occur


This is called an alternative hypothesis
Alternative to the null hypothesis

Example: When told to queue in a bank, more older people
than younger people obey.

In pairs, discuss how you could test this hypothesis?

Think of the difficulties of recording data when using this
example

Operationalising variables – making it measurable in
practice

When told to queue in a bank, more older people
(45+) than younger people (under 45) obey.
Task 1

Provide 2 alternative hypotheses ensuring they are
operationalised

Participants who have been trained in a memory
improvement strategy will correctly recall more items
from a list than participants who have not been
trained
Why methodology is
important

Methodology – how psychology is carried out. To
ensure that results and conclusions are secure

'Secure'- involves issues (evaluation points
generalisability, validity, reliability, objectivity,
subjectivity, credibility and ethics.)

To obtain 'secure' data methodology should be
prepared carefully.
1.2.1 designing and conducting
questionnaires and interviews
Questionnaires: TASK 2 in pairs discuss the answers to
these questions
•
What type of data can questionnaires gather?
•
What type of questions can be asked?
•
How can a questionnaire be completed (I.e. Ways in
which the participant can receive the questionnaire)
•
Why is it a useful method to collect data?
•
What are the problems with this method?
Questionnaires – general
points

Gather personal data: attitudes, opinions, lifestyles. Any aspect of a
person's life

Gather a large amount of information from a large sample in a
relatively short amount of time

Can be administered by post, email, face to face, or online

More straight forward questions come first followed by more in-depth
questions

For ethical reasons – the questionnaire shouldn’t be too long and
should not be too personal (i.e. you wouldn’t want someone to
become distressed by the questions). Questions should only ask what
the researcher really needs to know.

Pilot study: Initial study run with a few participants to test the questions
and check their clarity and suitability. In light of the pilot, changes can
be made.
Types of questions

You can gather different types of data

Quantitative and qualitative questions

Quantitative – Information that is or can be converted
to numbers

Qualitative – information that is non-numerical prose

Closed questions

Preset fixed answers –
respondent much choose the
answer that is the closest match
to their opinion

Forced choice
Likert scale: named after
Rensis Likert. It follows this
format. Strongly disagree
to strongly agree. Can also
be referred to as ranked
scale

Rating Scale
Rating Scale
Task 3

Write out one example for each of the item types
given below.

Focus on a questionnaire to find out about eating
habits of pupils in a school

1. Likert-type

2. Rating scale

3. Open question
Closed questions – strengths
and weaknesses
Strengths


Easy and quick to answer.
Standard replies (gather
quantitative data that is
easy to compare and
analyse)
If repeated it is likely to
obtain the same responses
(reliable)
Weaknesses

Forces a choice so may not
reflect the respondents true
opinions/feelings or thoughts
(not valid)

Unsure can mean ‘don’t
know’ or sometimes ‘yes’
and other times ‘no’.
Therefore answers mean
different things to different
people – not comparable.
(no producing valid data)

Open-ended questions (open questions)

E.g “Can you tell me how happy you feel right now?”

“What makes you happy?”

These questions allow he respondent to state their
attitudes and opinions

Answer is left open for the respondent to give their views
Strengths
Weaknesses
Participants are able to give their own
opinions and therefore more detailed. They
are not forced into specific answers. Richer
and more detailed data.
Difficult to analyse as all answers may be
different and therefore it is difficult to
compare answers. Subjective
interpretation
Also difficult to display results. Data is
qualitative so you can’t use numbers to
calculate averages or draw
tables/charts
Questions can be interpreted by
respondents. i.e. What does prejudice
mean to you? They can explain what it
means to them personally and what they
really think. More valid as they enable
respondents to talk about what they
‘really’ think.
Respondents often fail to complete their
answers. They take longer and it is more
difficult to think of the answer.
Task 4

What are the differences between open and closed
questions?
Open-ended
questions
Term (i.e.
whereas, in
contrast,
similarly etc.)
Closed
questions
Task 5

Explain, using examples, the difference between
closed and open-ended questions (6 marks)

To hand in
Quantitative and qualitative
data

Questionnaires can gather both sets of data, as can interviews.

This is called a mixed method

Some research only used one type of data

Quantitative: Involve numbers (percentages, number of yes/no
answers)


Closed-questions are used to produce quantitative data
Qualitative: ideas, opinions and attitudes

Open questions produce qualitative data
Task 6: Decide whether these are
open/closed and what type of data is
produced (qualitative or quantitative?

How would you describe obedience to authority?

Do you agree that everyone should have the same
job? Yes or no?

Rate on a scare of 0-5 (0=not at all and 5= totally) how
much you agree with the statement ‘everybody
should have the same job opportunities’.

What do you think about people who discriminate
against others because of their race?

How happy are you? Please rate on a scale from (0
very sad to 5 very happy)
Strengths and weaknesses of
quantitative data
Strength



Quickly and easily analysed as
averages, percentages and
other statistics can be
calculated also the data can
represented in graphs and
tables (efficiently
communicated to others)
Reliable – controls are put into
place; questions are
standardised therefore the test
can be repeated and provide
the same results
Objective data – numbers are
numbers and therefore not
open to interpretation
Weakness

Data may not be valid as the
respondents have a forced
choice of answer

They may answer it quickly and
not check their answers
(validity)

Respondents may not the tell
the truth
1.
Social desirability
2.
Demand characteristics
3.
Response bias
* For definitions refer to the next
slide

Social desirability

Tendency to answer in a way that is socially acceptable meaning the
data is not valid

Demand characteristics

Forced questions may hint at the aim of the questionnaire

Respondent may want to help the researcher and give them the answers
they think they want

Or might no want to help in which case they may give different answers

Responses lack validity as the are not ‘true’ answers

More likely when using quantitative data – with a clear aim and
hypothesis there may be clues about what the researcher is investigating.

Question construction

Language can’t be ambiguous or too technical

Questions should not lead or mislead the participants into giving a
particular answer

Response bias

If all the statements are worded favourably or unfavourable the
respondents can slip into agreeing or disagreeing with all of them. To
resolve this the statements should be reversed or mixed up

E.g. Pets make people happy-----------Pets do not make people happy
Strengths and weaknesses of
using qualitative data
Strengths

Detailed information which
allows in depth analysis.
Provides useful understanding

More validity than quantitative
data as respondents can say
what they really think about an
issue
Weaknesses

Data is harder to analyse in order
to compare responses. Answers
might be different and therefore
difficult to categorise and
summarise.

Data is considered subjective as
the meaning found in prose can
be open to interpretation

Data may be difficult to gather as
respondents may be reluctant to
give in depth responses. i.e.
missing out open-ended questions
and answering the yes/no
questions instead
Task 7

Paragraph - To EXPLAIN the difference between
qualitative and quantitative data

In your own words define:

Social desirability

Demand characteristics

Response bias

Provide an example of a way you can avoid response
bias when constructing questions for a questionnaire:
Methodological terms
covered so far – ensure you
understand these

Terms about questionnaires: pilot study, Likert-scale
questions, ranked scales, personal data, respondent,
open questions and closed questions

Types of data: qualitative and quantitative

Evaluation terms: validity, reliability, objectivity,
generalisability, and credibility

Terms about bias in studies: social desirability, demand
characteristics, response bias

Terms to control bias: controls, standardised instructions

Pilot study
Evaluating questionnaires as
a research method

We can evaluate questionnaires according to validity

Construct validity: the questions must measure what they
are supposed to measure

Internal validity: no other variables (except the IV) could
have caused the effect

Ecological validity: uses the respondent's natural setting
And results can be generalised to other settings.

Predictive validity: results would predict a real life situation
and

Demand characteristics and social desirability
Evaluating questionnaires as
a research method

Questionnaires can be evaluated by considering reliability

If the questionnaire was carried out again, would the same results
be found?

Closed questions have forced choice answers- reasonably
reliable

Questionnaires are set out and repeated exactly (standardised) –
this is a condition for reliability

Open questions allow for opinions to be given- so are less reliable
Evaluating questionnaires as
a research method

Objectivity/subjectivity

Objectivity – avoid bias from the researcher’s own opinions and
understanding

Experimenter/Researcher effects must be controlled for


i.e. tone of voice, clothes work or gender
Subjectivity is to be avoided

When gathering data

When analysing data

Credibility

Data – credible when valid (true to like), reliable (found more than
once), generalisable and agree with common sense
Task 8

Give one strength and one weakness of questionnaires
as a research method (4 marks)

2 marks for strength

2 marks for weakness

All A03 - evaluation
Sampling

Generalisability- results are generalisable, when they
come from good sampling that is representative of the
target population, so it can be said that what was
found is 'true' of all the others who were not in the
sample

Therefore the sampling technique used plays a very
important part in whether we consider results to be
generalisable or not.

If the sample gathered is not representative because
of an over/under-representation of a particular type of
participant, a sample bias will occur
Sample techniques
1.
Random sampling: most likely way of recruiting a
representative sample (still possible that it will be
unrepresentative as you may randomly pick un an
unrepresentative sample)

Everyone has an equal chance of being selected

Computers – random sequence of numbers (i.e. all
members from target population is given a number
and then a generator randomly selects numbers)

Names in a hat – draw at random
Random sampling evaluation
Strengths
Weaknesses
Low bias – everyone has an
equal chance of being
selected
Cannot be certain that the
sample is representative of
all groups
Good generalisability – low
bias and more likely to be
representative of the target
population
Difficult to access all he
population so that random
sampling can take place
Sample can be checked
mathematically for bias
2. Stratified sampling
If the target population has noticeable characteristics that
need to be proportionately represented in the sample,
stratified sampling can be used.
A stratified sample is a mini-reproduction of the population.
Before sampling, the population is divided into characteristics
of importance for the research. For example, by gender,
social class, education level, religion, etc. Then the
population is randomly sampled within each category. If 38%
of the population is college-educated, then 38% of the
sample is randomly selected from the college-educated
population.
Stratified sampling evaluation
Strengths
All relevant groups will have
at least some
representation (good
generalisability)
It is difficult to know how
many of each group is
needed in order to
represent the target
population accurately
Limits the numbers of
participants needed
Relies on researchers
knowing all the required
groups; forces choice of
participants and
proportions so can lead to
bias by excluding certain
people

3. Opportunity sampling

This is where you make use of the participants
available

i.e. investigating passers by on the street

Going into a classroom and asking students in the
room to complete a questionnaire

Limited control over who is recruited. Not everyone in
the target population has an equal chance of being
selected
Opportunity sampling evaluation
Strengths
Weaknesses
More ethical as the
researcher can judge if the
participants is likely to be
upset by the study or if they
are too busy
They may be a selfselecting group i.e. not
working so available in the
day
Easier and quicker to
May not be representative
organise – efficient and the so may be a biased sample
researcher has more control (low generalisability)

4. Volunteer sampling

Advert in a newspaper or poster in the common room

Volunteers are self-selecting because they choose to
take part

Often a certain type of participants may choose to
take part which can lead to sample bias
Volunteer sample evaluation
Strengths
Weaknesses
Ethical – people volunteer
of the own free will
Only certain types of
people may volunteer –
bias. (Low generalisability)
More likely to cooperate,
which means here may be
less social desirability
May take a long time to get
enough volunteers
Task 9

Answer this question---
Task 10

To EVALUATE sampling techniques (8 marks) Homework

4 marks – A01 Describe

4 marks – A02 Evaluate
Interviews are different from questionnaires as they involve social interaction.
Researchers can ask different types of questions which in turn generate different
types of data. ,For example, closed questions provide people with a fixed set of
responses, whereas open questions allow people to express what they think in
their own words.
Sometimes researchers use an interview schedule. This is a set of prepared
questions designed to be asked exactly as worded. Interviews schedules have a
standardised format which means the same questions are asked to each
interviewee in the same order.
Quite often interviews will be recorded by the researcher and the data written up as
a transcript (a written account of interview questions and answers) which can be
analysed at a later date.
The language the interviewer uses should be appropriate to the vocabulary of the
group of people being studied. For example, the researcher must change the
language of questions to match the social background of respondents' age /
educational level / social class / ethnicity etc.
It should be noted that interviews may not be the best method to use for
researching sensitive topics (e.g. truancy in schools, discrimination etc.) as people
may feel more comfortable completing a questionnaire in private.
Interviews take many forms, some very informal, others more structured.
Interviews

Page 44-45

Task 11 There are three types of interview. Complete
the table below using your textbooks
Type of
interview
Explanation
Brief evaluation
(strength and
weakness)
Evaluating the interview
method
When evaluating this method you can use the issues you
already know about (i.e. open/closed questions,
qualitative and quantitative data)
Strengths
Weaknesses
Answers can be explained in
detail – good method when in
depth and detailed data is
required
The interviewer may influence
the data which could result in
research bias
Valid data- interviewees can
used their own words and are not
as constrained by the questions
as they are in questionnaires
Analysis may be subjective and
the researcher’s views may
influence the analysis (down to
interpretation)
Comparing questionnaires
to interviews
Differences between the
questionnaire and interview
method

Task 12 – complete the table
Questionnaire
Term (i.e.
whereas, in
contrast,
similarly etc.)
Interview
Ethical considerations

Task 13 - Page 55 of e-textbooks

Summarise the four main principles

Respect

Competence

Responsibility

Integrity

What is the difference between the principles and the
guidelines?
Risk Management
There can be risk to participants, researcher and animals if they are
sued in a study. There can also be risks to the environment or
society.
 Risk therefore must be managed by looking at the highest risk first,
working down to the lowest level of threat.
 It is about looking at the probability of a threat happening against
the consequences.






Solutions:
Transference of risk – insuring against it happening
Mitigation – reducing the risk as far as possible
Acceptance – budgeting for the risk
BPS: The risk of harm must be no greater that what participants
would be exposed to in their ‘normal lifestyle’
Task 14

Task 14 - Why is risk management important when
designing a study in psychology?
Practice question
Many parents complain that their children watch too much TV. Imagine
that you have been asked to carry out a questionnaire to see whether
teenagers or their parents watch more hours of TV.

(a) Write an alternative hypothesis for your survey.(2)

(b) (i) Which sample technique would be used in your questionnaire?
(1)

(ii) Explain why you would use this technique. (2)

(c) With reference to your survey into television viewing hours,
explain two ethical guidelines that you would need to consider. (4)

(d) Provide one reason why a questionnaire may be more
preferable than an interview in this situation (1)
Analysis of quanitative data

LO:

To analyse quantitative data including measures of
central tendency (mean, median and mode),
measures of dispersion (range and standard deviation)
and graphs (bar charts and frequency tables)
Measures of central
tendency

Descriptive statistics include measures of central tendency which are
mode, median and mean average

Data analysed in such a way that it is clearly displayed and understood
(tables and graphs)

Examples:

Mode: The most common score in a set of scores

1 5 7 8 8 12 12 12 15 (mode is 12)

Median: The middle score in a set of scores (in order)

1 5 7 8 8 12 12 12 15 – median is 8

1 5 7 8 8 11 13 14 15 20 – median is 9.5 (8+11)/ 2 =9.5

Mean : arithmetical average (adding all the scores in the set and dividing
by the numbers of scores in a set)

1 5 7 8 8 11 13 14 15 20 – mean is 10.2
Measure of central
tendency
How is it measured?
Advantages
Mean
Add up all the numbers and
divide by the number of
numbers
Makes use of the values of Not appropriate for
all the data
categories
Disadvantages
Can be unrepresentative
if there are extreme
values
Median
Place all values in order from
the largest to smallest and
select the middle value.
Not affected by extreme
scores
Mode
Value that is most common
Useful for data in
categories e.g. favourite
colour
Mode = the colour that
received the most votes
e.g 2, 4, 5, 6, 9, 10, 12
mean= 6.86
2, 4, 5, 6, 9, 10, 29
mean = 9.42
Not as ‘sensitive’ as the
mean because not all
values are reflected
Not a useful way of
describing data when
there are several modes.
12 people – yellow
12 people – red
10 people - purple
Measures that can be used
depending on the data
Categories
(nominal i.e.
Yes/no)
Mode
Mean
Median
a
Ranking or
rating
(ordinal i.e.
Likert)
Interval data
(equal
intervals
between
data I.e.
height/time)
a
a
a
a
a
Task 15

For each of the following sets of data (a) calculate the
mean, (b) calculate the median, (c) calculate the
mode

2, 3, 5, 6, 6, 8, 9, 12 ,15, 21, 22

2, 2, 4, 5, 5, 5, 7, 7, 8, 8, 8, 10

2, 3, 8, 10, 11, 13, 14, 14, 29
Measures of dispersion

Calculates the spread of score in a data set

Range – The range is a measure of dispersion, found by
finding the highest score/number and taking away the
lowest score giving the difference between the two.

5 7 8 8 12 12 12 15 – range is 10 (15-5)

Influenced by extreme scores so it may not always be
useful

Doesn’t tell us if the scores are bunched around the
mean score or more equally distributed

1 7 8 8 12 12 15 16 55 (55-1 = 49)
Measures of dispersion

Standard deviation (use page 49 to help you)

Measure of how far scores vary from the mean
average.

The higher the standard deviation, the greater the
spread of scores around the mean value

Add up the differences squared for all the scores and
then divide that number by the number of scores
minus 1. Then finally, find the square root and you have
the standard deviation
Task 16

Using the example on page 50 and the steps 1-5

Calculate the standard deviation for these scores:
Score (x)
Mean
Deviation
Squared
deviation
6
9
4
8
3
n-1= ? (n: number
of scores)
Sum of deviations
squared:
Standard deviation: ______
Summary tables

Summary tables represent measures of central
tendency and dispersion clearly

TASK 17 (Use page 50 to help you)

What comments can you make about
Table showing the self-rated obedience
scores of males and females
this data?
Males
Females
Mean
obedience
rating
4.1
7.4
Median
obedience
rating
4
7
Mode
obedience
rating
4
6,7,9
Range of
obedience
ratings
3
3
Standard
deviation
1
1.2
Bar graph

Useful to illustrate summary data

Bar chars are used to present data from a categorical
variable such as the mean, median or mode. Categorical
value is placed on the x axis and the height of the bars
represent the value of the variable.

TASK 18 Sketch a bar graph

A bar graph showing the mean self rated obedience
scores (from the table on the previous slide)

All graphs need titles and ensure for a bar graph you
include a space between each bar.
Frequency tables

A frequency table records the number of times a score
is found, rather than the score itself being displayed
against each participant

Useful as the distribution can be seen in table form.

A histogram or frequency graph can be used to
display the data
Table to show frequency of self rated
obedience scores
Self reported
obedience scores
Frequency
1
2
2
5
3
4
4
2
5
3
Histogram/frequency graph

This type of graph is used to present the distribution of
the scores. Unlike a bar chart, where the bars a
separated by a space, the bars on a histogram are
joined to represent continuous data rather than
categorical data.

The values are presented on the x-axis and the height
of each bar represents the frequency of the variable

TASK 19

Sketch a histogram based on the data in the previous
slide
Analysis of qualitative data

Qualitative data are in the form of comments or opinions, so need to be
summarised to make them manageable and clear. This is done by
thematic analysis, generating themes from data (i.e. patterns and trends
within data)

How frequent or central to the text the theme is depends on the opinion of
the researcher

E.g. finding that most respondents on a questionnaire comment of liking
people of the same age. Theme here is age.

The researcher then develops these themes into ‘codes’ which represent
the categories of themes found. The research will then use the codes to
analyse the data gathered and search for instances where it appears in
the data

This is reviewed and changed until the themes can be stated, supported
and used as a summary of the data
Analysis of qualitative data Evaluation

Analysis of qualitative data is considered to be subjective
(down to the interpretation of the researcher which can lead
to research bias) and therefore not scientific.

Reliability of the data can be checked by using more than
one researcher (comparisons can be made)

If the data is analysed without preconceptions and is not
interpreted (i.e. the respondents ‘meanings’ are recorded
then the data can be considered valid.) Validity can be
questioned as researchers often do not explain fully how they
arrived at the themes.

However it does yield very detailed and meaningful
information that cannot be gathered with quantitative data.
Task 20 – thematic analysis

E-book- pg.54

In your own words, explain thematic analysis (2 marks)

Explain what is meant by the inductive and deductive
approach (4 marks)