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SURVEYS AS A
METHOD OF DATA
COLLECTION
This file contains hyperlinks to take you to the various linked sections
BEGIN
WHAT WILL BE COVERED
Outline:
1. Introduction:
them?
2. Examples of real surveys:
3. Conducting surveys:
- What are surveys and when would you want to use
- Some common Australian surveys
- How do you design and carry out a survey?
4. Developing survey questions: - Eliciting useful data
5. Sampling:
- How do you sample the population of interest?
6. Errors and bias:
- Making sure your data is good quality
7. Considerations collecting data: - Some key things to be aware of
8. Analysis and reporting:
9. Further reading:
- Processing and presenting your data
- Other good sources of information
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1. INTRODUCTION:
What are surveys and when would you want to use them?
What are surveys?
Surveys are a way of gathering primary data from a human population of interest (e.g.
individuals, households, farms, businesses) by asking a standard set of questions to a sample
of the population
“Surveys provide a means of measuring a population’s characteristics, self-reported and
observed behaviour, awareness of programs, attitudes or opinions, and needs. Repeating
surveys at regular intervals can assist in the measurement of changes over time. These types
of information are invaluable in planning and evaluating government policies and programs.”
(http://www.qgso.qld.gov.au/about-statistics/survey-methods/)
Hence key issues involved include:
 Who is the population and how can you obtain the data you need?
 Asking clear and specific questions,
 Robust sampling methods to enable statistically strong study conclusions.
... We will explore these types of issues in the presentation.
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1. INTRODUCTION:
What are surveys and when would you want to use them?
What are surveys?
Difference between a survey and a census:
 A survey samples a subset of a population of interest, whereas
 A census seeks to sample the entire population of interest
For a probability survey, the survey sample is chosen objectively so that it statistically represents
the wider population (i.e. no bias) – “each member of the population will have a known non-zero
chance of selection” (http://www.qgso.qld.gov.au/about-statistics/survey-methods/)
... This then allows you to generalise the survey findings to the wider population (the ultimate goal)
Total population
Good sample
Poor sample
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1. INTRODUCTION:
What are surveys and when would you want to use them?
Purpose of surveys
There are many possible purposes of surveys, including:
 Collecting baseline data, or following-up for a time series,
 Comparing two groups (these can be such things as clinical trials),
 Evaluating the effect of interventions (eg education, policies or programs),
 Identifying needs for funding or resource allocation, or
 Tracking of population characteristics in society (e.g. employment, awareness of
topics, internet access, etc).
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1. INTRODUCTION:
What are surveys and when would you want to use them?
When to use a survey?
Surveys are resource and time-intensive (including design, identifying and distributing to
potential respondents, effort for respondents to complete survey, time to wait for responses).
Hence need to consider whether a survey is the best strategy for gathering the data you need
e.g. does relevant data already exist in other published reports, on the ABS website, etc?
However, often other people’s data may not meet your specific research needs, so a survey
may be required.
... If so, then there’s several things you need to consider at the outset.
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1. INTRODUCTION:
What are surveys and when would you want to use them?
Things to consider for doing a survey*:
Practicality
• Can the information be collected cost effectively and accurately via a survey?
• How complex and how sensitive is the topic?
• Do respondents have access to the required information? Will they be willing to supply it?
• Will their responses to the questions be valid?
Timing
• When is the information required?
• Is enough time available to ensure that data of sufficient quality can be collected and analysed?
• When is the best time to conduct the survey? (eg growing seasons, holiday periods).
Survey requirements
• What will the survey findings be used for (eg to target program improvements)?
Ensure to collect data that will enable you to report with sufficient statistical accuracy,
and focus on sub-groups of interest (eg geographic areas, age groups, sex, industry,
size of business)
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*Ref: http://www.qgso.qld.gov.au/about-statistics/survey-methods/
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1. INTRODUCTION:
What are surveys and when would you want to use them?
Things to consider for doing a survey*:
Accuracy
• What level of error is acceptable? (depends what survey results will be used for)
Frequency
• Will the survey be repeated? How often?
Resources
• Are the necessary financial, staff, computer or other resources available?
Legislative powers
• Does your organisation (eg university, government department/agency) have authority to
collect the information through a survey? This is linked to the final issue:
Ethical considerations
• All research involving human subjects must follow strict ethics procedures
(explained more later in the presentation).
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*Ref: http://www.qgso.qld.gov.au/about-statistics/survey-methods/
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2. EXAMPLES OF REAL SURVEYS:
Some common Australian surveys
Monthly population survey - Australian Bureau of Statistics (ABS):
This surveys 35,000 households every month on issues including employment, education, the
environment, conditions of employment, and child care arrangements.
The main component is the Labour Force Survey, which is where the national monthly
employment figures come from!
Note that this is a survey of households
See: http://www.abs.gov.au/websitedbs/d3310114.nsf/home/current+household+surveys
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2. EXAMPLES OF REAL SURVEYS:
Some common Australian surveys
Business surveys - Australian Bureau of Statistics (ABS):
Cover all manner of topics
Note that this is a survey of businesses
See:
http://www.abs.gov.au/websitedbs/d3
310114.nsf/home/survey+participant
+information
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2. EXAMPLES OF REAL SURVEYS:
Some common Australian surveys
Business surveys - Australian Bureau of Statistics (ABS):
... Zooming in on agriculture-related surveys:
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See:
http://www.abs.gov.au/websitedbs/d3310114.nsf/home/
survey+participant+information
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3. CONDUCTING SURVEYS:
How do you design and carry out a survey?
Steps in the survey process:
1. Design
and plan
survey
2. Design
questions
3. Pilot test
and adjust
survey
4. Conduct
survey
5. Data
analysis and
reporting
Repeat steps
if needed
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Adapted from: http://www.qgso.qld.gov.au/aboutstatistics/survey-methods/
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3. CONDUCTING SURVEYS:
How do you design and carry out a survey?
Step 1. Design and plan survey:
Key things to do at the first step:
 Define purpose and objectives of study
 Eg to describe characteristics of a population (individuals, households,
businesses, ...), to compare different groups (eg the target group for a program
vs a control group), or to gain feedback from a group of people about their views
 Identify the output required (eg what types of data, charts/tables do you want to
produce at the end?)
 Define target population and sampling strategy
 Decide data collection method (eg paper, online, telephone or in-person interview)
 Develop survey procedure
 Obtain ethics approvals (from appropriate university or government
department ethics committee)
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3. CONDUCTING SURVEYS:
How do you design and carry out a survey?
Step 1. Design and plan survey:
Target population: The target population needs to be defined carefully and explicitly eg what
demographic characteristics define the target population? In a rural population, what is
meant by ‘rural’? What is the geographical area of interest?
Data collection methods:
Method
Pros
Cons
paper
Least expensive; respondents have time to complete
Potentially high non-response rate;
questions must be kept simpler
online
Can have more complex questions; relatively convenient
May be ignored, but easy to re-send
for respondents
telephone
Can have more complex questions; interviewers can
interview
improve non-response rate
in-person
Can have more complex questions; interviewers can
interview
improve non-response rate
Moderately expensive
Most expensive
http://www.qgso.qld.gov.au/about-statistics/survey-methods
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3. CONDUCTING SURVEYS:
How do you design and carry out a survey?
Step 2. Design questions:
Key considerations:
 Survey questions need to measure things accurately, and it takes a lot of work and
careful design to write questions that can do this – this is not trivial!
 For example, questions need to be clear to all potential respondents, not ‘leading’
questions (i.e. worded in a way that may bias the response), and allow for robust
data to be collected
 Questions MUST be designed in such a way that they have reliability and validity
... Question design is covered in more detail in Section 4
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3. CONDUCTING SURVEYS:
How do you design and carry out a survey?
Step 3. Pilot test and adjust survey:
What needs to be done:
 Pilot test the entire survey with a small number of respondents from the target population
(i.e. ‘real’ respondents, although you may not be able to actually use this data)
 You want to check how respondents find the questions and the survey as a whole
 eg are their any problems with the layout or structure? Do the questions all make
sense? Is the length of the survey manageable?
 Find out afterwards what the pilot respondents though of the survey
 Modify survey as appropriate (eg procedures, questions, structure), and repeat the first
step of design and planning if needed – this is not a bad thing, it’s extremely positive
because you will get better data and have more robust findings!
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3. CONDUCTING SURVEYS:
How do you design and carry out a survey?
Step 4. Conduct survey:
What’s involved:
 Finalise survey and procedures to be conducted in the field
 Finalise sampling strategy and ensure recruitment strategy clearly identified (e.g. contact
lists, places survey will be advertised)
 Train interviewers (if survey to be conducted in person using research assistants)
 Distribute survey through data collection methods decided in the first step of the process
(eg mail out, online, in person)
 Wait for results to arrive, meanwhile monitor process – eg are there any problems in the
survey completion? Have any respondents contacted you with questions or concerns
either before or after completing the survey? How will their concerns be
addressed – both in terms of the data collection process as well as in
terms of any ethics issues raised?
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3. CONDUCTING SURVEYS:
How do you design and carry out a survey?
Step 5. Data analysis and reporting:
How do you go about this?
 Prepare tables and files to enter data into (eg MS Excel spreadsheets)
 Code and edit data (eg fill gaps, check data quality, convert qualitative responses to
numerical scales if required)
 Analyse data eg count responses, calculate statistics (eg %’s, averages, standard errors)
 Prepare tables and charts to present data
 Prepare reports and/or papers to report on survey results
 Evaluate and reflect on the survey process – What worked well? What didn’t work so
well? What would you do differently next time? Can your survey be used again in the
future (by yourself or others) eg to develop a time series of the same
parameters?
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4. DEVELOPING SURVEY QUESTIONS:
Eliciting useful data
Why does this matter?
A survey is used to measure something, just like if you were using a thermometer or scales in
an experiment in a lab – so it needs to be accurate otherwise you’ll get poor readings and
your data won’t make sense!
More specifically, we need to make sure our survey has reliability and validity
 Reliability means that you get the same result if you repeatedly measure the same
property – i.e. that a survey question means the same thing to all respondents.
 Validity means that the survey question accurately measures what it intends to
measure
Both reliability and validity are essential – a classic example of why this is important is the
case of faulty bathroom scales. The scales might consistently read 70kg (it is reliable) but
they may be badly calibrated, and your real weight is 60kg (hence the
reading is not valid).
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4. DEVELOPING SURVEY QUESTIONS:
Eliciting useful data
How do you develop good questions?
This is a skill and takes a lot of time to develop, edit and refine the questions
Some general tips are:
 Focus clearly on the goal of the survey – critically reflect on how each question will
help you address that goal
 Avoid asking unnecessary questions – a good technique is to draft the charts and
tables that you want to make from the data to help clarify which questions are most
important and which ones are not
 See if you can find previous surveys as examples to help you build yours – this can
be very useful to build on and to get a sense of how to write good questions
 Try to maintain a parallel structure for all questions – this significantly
improves the ability of respondents to follow and effectively respond to
the survey.
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4. DEVELOPING SURVEY QUESTIONS:
Eliciting useful data
Practical tips:
Some practical tips are:
 Avoid leading questions – i.e. ensure it doesn’t seem like you’re expecting a certain
response, but give a full range of options for respondents. For example, instead of
asking respondents to agree or disagree with a statement, provide a full range of
possible responses such as: not at all, a little, somewhat, quite a bit, extremely
 Keep questions simple
o Avoid questions that should be two questions
o Avoid using complex words, technical terms, acronyms or jargon. Instead, use
language that is commonly used by the respondents.
 If you ask about a past experience then give a time boundary / reference period. Also,
note that recent recall will be sharper eg ‘Have you been to the movies in
the last month?’ Rather than: ‘How many times did you go to the movies
in the last year?’
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oqi.wisc.edu/resourcelibrary/uploads/resources/Survey_Guide.pdf
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4. DEVELOPING SURVEY QUESTIONS:
Eliciting useful data
Practical tips:
More practical tips:
 Avoid using complex words, technical terms, jargon, and phrases that are difficult to
understand. Instead, use language that is commonly used by the respondents.
 For example*:
Instead of using:
Use:
Employment
Work
Exhausted
Tired
Regarding
About
Occupants of this household
People who live here
Your respondents to this survey
Your answers
Work-related employment issues
Job concerns
Health care provision
Providing health care
*Sourced from:
oqi.wisc.edu/resourcelibrary/uploads/resources/Survey_Guide.pdf
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4. DEVELOPING SURVEY QUESTIONS:
Eliciting useful data
Response format:
Questions may be open-ended in allowing respondents to answer a question in their own words
 This has advantages such as: of gaining richer answers and insights into the
respondents views, and the possibility of unanticipated answers
 However, a disadvantage is that it is more difficult to interpret and analyse this data
Questions may also be closed, in that they provide a pre-defined set of categories and the
respondent chooses the answer that best represents their view (eg very dissatisfied, somewhat
dissatisfied, neither satisfied nor dissatisfied, somewhat satisfied, very satisfied)
 This has advantages that: respondents may find it easier and less time-consuming to
choose a response on a scale, and it is more straightforward to analyse this type of data
 However, a disadvantage is that it confines the range of responses to
pre-defined categories which must be chosen very carefully to be
appropriate and intuitive to respondents
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5. SAMPLING:
How do you sample the population of interest?
Definitions:
 Target population: The group of people or organisations whose activities, beliefs or
attitudes are being studied
 Sample: The subset of the target population that forms the set of respondents to the
survey
 Sampling frame: This is essentially the boundaries that you draw around the target
population to define who the possible set of sample subjects may be i.e. By what
criteria do you ‘bound’ the population? For example, this could constitute a telephone
directory, or a list of business or organisations or households. Need to consider: is
this list available, and how current is it? MUST avoid sending to deceased people or
non-existent organisations (ethical practice, plus will affect calculated response rate)
 Respondent: An individual or organisation providing answers to survey
questions
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5. SAMPLING:
How do you sample the population of interest?
Methods of survey sampling:
This refers to the way that respondents within the sample are selected from the target population
There are two broad types of sampling strategies:
 Probability sampling – each member of the population has a known (non-zero) probability
of being selected in the sample (e.g. choosing names randomly from a phonebook)
 Non-probability sampling – the probability of each member of the population is not known
and/or we do not know whether each member has a non-zero chance of being selected
Probability sampling has the advantage that survey statistics for the population can be easily and
reliably calculated. However, it may not be possible to build knowledge of the entire population (e.g.
all businesses in the country), or it may just be prohibitive in terms of the work required to do so.
Non-probability sampling has advantages of cost and convenience. However, the
main drawback is that sample statistics are likely to differ from the characteristics
of the actual broader population, and it is hard to know by how much.
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5. SAMPLING:
How do you sample the population of interest?
Probability sampling:
In probability sampling, every observation in the population from which the sample is drawn has a
known probability of being selected into the sample
When that probability is the same for every observation in the population, the sample is an equal
probability sample. These samples have certain desirable properties; for example, the simple
formulas for computing means, standard deviations, and so on can be applied to estimate the
respective parameters in the population.
Different types of probability sampling are:





Simple random sampling
Stratified sampling
Cluster sampling
Multistage sampling
Systematic random sampling
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5. SAMPLING:
How do you sample the population of interest?
Types of probability sampling:
Simple random sampling:
 This occurs if:
o For a population (N) and a sample (n),
o All possible samples (n) of the population (N) are equally likely to occur
 For example, a random sample from a telephone book is an example of this.
Stratified sampling:
 This is done when the population involves groups with differing characteristics that of
relevance to the study, and you are interested in having sufficient resolution in your data to
analyse survey data for different types of respondents (e.g. respondents in different
geographical locations such as neighbourhoods within a city; by age; level of education; ...)
 The population is divided into groups or ‘strata’, and then respondents
are sampled within these strata
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Reference: http://www.qgso.qld.gov.au/about-statistics/survey-methods
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5. SAMPLING:
How do you sample the population of interest?
Types of probability sampling:
Cluster sampling:
 This is a technique where each member of the population is assigned to a group (a
‘cluster’), and a set of clusters are chosen, from which individuals are then surveyed.
 Clusters basically represent ‘small scale’ versions of the population i.e. each cluster
contains heterogeneous individuals similar to the population (although the mean of the
clusters should be the same). This differs to stratified sampling where separation by strata
aims to tease apart heterogeneity in the population in key ways that are likely to affect the
results.
 Cluster sampling can have less precision than random sampling, but it can allow you to
greatly increase the sampling size for the same effort/budget. If you really need a larger
sample size but don’t have the budget to do a comprehensive simple random sample for a
sample that size (and you don’t mind the loss in precision) then cluster
sample may be useful
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Reference: http://www.qgso.qld.gov.au/about-statistics/survey-methods
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5. SAMPLING:
How do you sample the population of interest?
Types of probability sampling:
Multistage sampling:
 This applies multiple stages of cluster sampling in successive stages
 For example, if a large household survey is to be conducted (e.g. across QLD) then you
could divide the population into districts (e.g. ABS districts) then choose a sample of those
districts. Within the chosen districts, you may then sample a set of neighbourhoods. Finally,
within each neighbourhood, you then sample individual households.
 The advantage of this method is that it can reduce the costs of a large-scale survey, and
means you only need to develop the sampling frame at each stage as required, rather than
for the whole population at the outset.
Systematic random sampling:
 First you need to define the sample size and create a list of the entire population. You then
randomly select the first sample element, and then take the kth next
element on the list, and continue until you reach your desired sample size.
 As long as the list does not contain hidden order, this is very much like
simple random sampling, but is just a bit simpler
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Reference: http://www.qgso.qld.gov.au/about-statistics/survey-methods
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5. SAMPLING:
How do you sample the population of interest?
Non-probability sampling:
Non-probability sampling is non-random sampling. It is used largely out of convenience and often
either as an exploratory method or for looking at relationships between variables. The main
drawbacks are that the relationships between the survey sample and the total population is not
measureable and it is not possible to determine bias. Some methods are:
Voluntary sample:
 Respondents self-select into the survey (often people with a strong interest in the topic)
 E.g. Responding to an online poll
Convenience sample:
 Respondents are people that are easy to reach
 E.g. university students sampled for a study conducted at their university
Purposive sampling:
 Respondents are purposively selected because the belong to a particular
category of interest to the researcher (e.g. a particular demographic)
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5. SAMPLING:
How do you sample the population of interest?
Sample statistics:
The purpose of doing a survey is to measure some attributes of a population by calculating these
values for a sample of the population. This is done by calculating sample statistics that ideally
reflect (or closely approximate) the wider population.
 Population parameter – A population parameter is the true value of a population attribute.
 Sample statistic – A sample statistic is an estimate of a population parameter, based on
the survey sample
For example, you may want to find out the percentage of dairy farmers in Australia that support a
new government policy on milk. You decide to do a survey of the 7,000 dairy farms in Australia. The
actual percentage is a population parameter (i.e. the actual percentage of the 7,000 farms if you
were to ask every one of them). The estimate of that parameter gained through a survey is a sample
statistic (calculated through your survey of a smaller sample of the total population).
It is clear that “the quality of a sample statistic (i.e., accuracy, precision, represent ativeness) is strongly affected by the way that sample observations are chosen;
that is, by the sampling method.”
* http://www.qgso.qld.gov.au/about-statistics/survey-methods
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6. ERRORS AND BIAS:
Making sure your data is good quality
Sources of error :
Errors with surveys can be divided into two types:
 Sampling error – this arises because a survey samples a subset of the population
 Non-sampling error – all other errors that can occur during a survey
Estimates of sampling error (e.g. standard error) can be calculated, and will vary with:
 Sample size (a greater size will reduce the sampling error)
 Variability in the population (sampling error will increase if the responses of interest
vary greatly in the population)
 Sample design (this affects whether or not standard errors can be calculated – i.e.
whether or not probability sampling was done)
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6. ERRORS AND BIAS:
Making sure your data is good quality
Non-sampling errors:
These cannot be measured, but they are just as important as sampling errors:
Source of error
Planning and
interpretation
Examples
Inadequate definitions of
concepts, terms or
populations.
Sample selection Inadequate list from which
sample is selected; biased
sample selection.
Survey methods Inappropriate method
(e.g., mail survey for a
very complicated topic).
Questionnaire
Loaded, misleading or
ambiguous questions,
poor layout or sequencing.
Strategies to minimise error
Ensure all concepts, terms and populations are
defined precisely through consultation between data
users and survey designers.
Check list for accuracy, duplicates and missing units;
use appropriate selection procedures
Choose an appropriate method and test thoroughly.
Use plain English, clear questions
and logical layout; test thoroughly.
Source: http://www.qgso.qld.gov.au/about-statistics/survey-methods
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6. ERRORS AND BIAS:
Making sure your data is good quality
Non-sampling errors (continued):
These cannot be measured, but they are just as important as sampling errors:
Source of Examples
error
Interviewers Leading respondents, making
assumptions, misunderstanding
or misrecording answers.
Respondents Refusals, memory problems,
rounding answers, protecting
personal interests or integrity.
Processing
Estimation
Errors in data entry, coding or
editing.
Incorrect weighting, errors in
calculation of estimates.
Strategies to minimise error
Provide clear interviewer instructions and
appropriate training, including exercises and field
supervision.
Promote survey through public media; ensure
confidentiality; if interviewer-based, use well-trained,
impartial interviewers and probing techniques; if
mail-based, use a well-written introductory letter.
Adequately train and supervise processing staff;
check a sample of each person’s work.
Ensure that skilled statisticians
undertake estimation.
Source: http://www.qgso.qld.gov.au/about-statistics/survey-methods
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6. ERRORS AND BIAS:
Making sure your data is good quality
Sources of bias:
Non-response to survey:
 Non-response occurs in almost all surveys, and may be due to factors such as
refusal, non-contact or language difficulties
 It is a source of bias if the characteristics of non-respondents differ to respondents
 It is good practice to try to minimise non-responses if possible (e.g. making callbacks to non-contacts or following up on refusals)
 Response rate is expressed as a %
Sampling frames:
 Bias can be introduced through imperfect sampling frames (which is common)
 E.g. telephone listings exclude those with ‘silent’ numbers, or
households without landlines which may lead to under coverage of
younger demographics
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6. ERRORS AND BIAS:
Making sure your data is good quality
Sources of bias:
Measurement error:
Poor measurement process can lead to bias and error e.g. if the survey is conducted in an
unsuitable environment, the questions are asked poorly, or the survey respondents are rushed
For example:
 Leading questions – this is where survey questions systematically lead respondents to
answer in a certain way by unduly favouring a particular response
o E.g. If the respondent is asked whether they are: ‘satisfied, dis-satisfied, or very
dis-satisfied’ then this will be likely to lead respondents towards dis-satisfied
responses because they are given two options for this
 Social desirability – this refers to the way that people like to portray themself in a
favourable light, so answers may be biased towards what is considered
to be acceptable
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7. CONSIDERATIONS COLLECTING DATA :
Some key things to be aware of
Response rates:
Survey response rates can be very variable, and depend on many factors such as: the topic of
the survey, whether the survey is conducted in a convenient way for respondents, the demand on
respondents (e.g. once-off for 20 mins vs 1 hour per session repeated every month for 6 months),
and whether respondents see that the survey is worthwhile and in their interests to participate.
Response rates can be improved by considering the needs of respondents carefully eg:
 Contacting respondents and conducting the survey in a way that is convenient to the
respondents (e.g. by telephone, online, paper, in-person as appropriate)
 Not expecting too much from respondents (eg in terms of time, effort, confidentiality)
 Following-up on non-responses
 Explaining how the survey is relevant to the respondents and how they stand to benefit
from the study, and/or what are the broader benefits to society of the study
 Explaining how the survey follows ethical research procedures (eg how
their data and identities will be protected, how the data will be used, who
they can contact if they have any grievances or further questions)
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7. CONSIDERATIONS COLLECTING DATA :
Some key things to be aware of
Ethics considerations:
Ethics approval from the relevant university or government ethics committee is required when
conducting surveys
This is because you are engaging with members of the public to collect data, and it is vital that
the public is protected in the way that the data is collected and used – at it’s core, this is about
human rights to safety, security, privacy, etc
This requires preparing the survey questions and procedure for consideration by the ethics
committee as to whether you meet the ethical requirements to conduct the study
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7. CONSIDERATIONS COLLECTING DATA :
Some key things to be aware of
Ethics considerations:
At the beginning of the survey you need to provide
some basic but essential ethics information such as:
•
•
•
•
•
Information on the project, why it is being
conducted, who it is being conducted by, and
what the results will be used for
Whether the survey is voluntary or compulsory
Information on who the respondent can contact
for further information or grievances
A statement that the survey has received ethical
clearance from the relevant ethics committee
A question about whether the person gives
permission for use of the data in other studies, or
to be re-contacted
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8. ANALYSIS AND REPORTING:
Processing and presenting your data
Simple analysis:
Survey statistics may be relatively simple to calculate in when you finally have the data
collected, but the main trick is everything up to this point – i.e. collecting data in a way that is
robust and methodologically sound
Descriptive statistics are often the first thing to calculate eg:
 totals, means, median, proportion of households
 plots of responses for a rating scale e.g. For questions with a numbered scale (such
as a Likert rating scale which is widely used) or using a qualitative response scale
(such as: very dis-satisfied, dis-satisfied, neutral, satisfied, very satisfied)
Each statistic (mean, total, etc) should be reported with its margin of error. This can be called
a ‘relative standard error’ (given as a percent)
Analysis involving more than one variable:
You may do more complicated statistical analysis such as: chi squared tests
of independence, analysis of correlations, logistic regression, etc
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9. FURTHER READING:
Other good sources of information
Useful websites:
http://www.qgso.qld.gov.au/about-statistics/survey-methods/index.php
http://stattrek.com/statistics/data-collection-methods.aspx?Tutorial=AP
http://www.nss.gov.au/nss/home.nsf/pages/NSS+Data+Quality+resources+landing+page
http://betterevaluation.org/
http://www.statcan.gc.ca/edu/power-pouvoir/toc-tdm/5214718-eng.htm
https://www.statpac.com/surveys/
http://www.abs.gov.au/ausstats/[email protected]/mf/1125.0 (Statistical skills for statisticians)
Key texts:
Schaeffer, N.C. and Presser, S. 2003. The science of asking questions.
Annual Review of Sociology 29:65-88.
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