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Summary Partial Exam 2 MCRS

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Weeks 6-12 of the Course. Everything relevant for the Second Partial Exam including both Methods and Statistics. Notes, examples, definitions, AND SPSS COMMANDS

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Subido en
6 de diciembre de 2020
Número de páginas
16
Escrito en
2020/2021
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Resumen

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METHODS 2
Surveys
- Surveys are a series of formatted questions delivered to a defiant sample
of people with the expectation of a response within a couple of days
- Surveys aim to capture the public opinion at a moment in time
- Advantages
o Relatively low cost
o Rapid data processing
o Relatively fast delivery
o Can research large populations
o Multiple methods of researching people (modes)
- Disadvantages
o Limited to the possible answers (doesn’t give explanations)
o No control over response rate
o Survey fatigue  increasing resistance
o Difficult to explore issues in depth
- Types of Surveys:
o Cross-sectional
 Asking one group of people the same questions at a point in
time
 Not expensive 😊 cannot determine causality ☹
o Longitudinal
 Observations made more than once, not able to detect causal
relationships, but does take time into account.
 Expensive ☹ gives some indication of causality 😊
 Types of Longitudinal Surveys:
 Trend = examines changes in a population over time.
Each study collects data from individuals, but it is not
clear why the change has occurred
o Different individuals over time
 Cohort = examines changes in a cohort over time.
Each study collects data from individuals within a
cohort, but still cannot determine causality because
the same individuals are not studied.
o Same type of people over time
 Panel = examines changes in the same individuals
over time (studied in waves). A more in-depth analysis,
still can’t establish causality
o Same individuals over time
- Surveys have low internal validity because there is no measuring of cause
and effect.
- Surveys have high external validity when the sample is large and random.
- Survey modes:

Survey Modes:
With Response Speed Cost Complexity
interviewers of

,: Questionnai
re
Face to Face Good Slow Very high Very high
By phone Reasonable Fast high Very high
Without
interviewers
:
Paper/pencil Low Low
Email/web low Very fast Very low Very high
- Types of Survey Questions:
o Dichotomous
o Open ended
o Multiple choice (mutually exclusive)
o Multiple choice (check any that apply)
o Rank order
o Likert scale
o Semantic differential scale
- Filter questions = routes respondents around questions that don’t apply to
them e.g. if yes go to Q16
- Problems with Survey wording:
o Overlapping answer options
o Double barrel questions
o Social desirability bias
 This is important to avoid when you are investigating
sensitive or controversial topics
 To Prevent:
 Indirect questioning
 Making them comfortable
 Give indication that it is okay to answer in a way that is
not socially desirable
- Pre-testing
o Its important to pre-test because surveys are expensive to put out
o Look at: survey wording, aesthetic design, logic and flow of wording,
clear meanings, length of time to complete survey
o How to pre-test:
 Ask respondents for feedback
 Cognitive interviewing
- Unit non response = not answering entire survey
- Item non response = respondent answering all but one question
Sampling
- Census = study of an entire population
- Parameter = describing a population
- Sample frame = list from which a sample is drawn
- Types of sampling:
o Probability Sampling = random selection of respondents
 Simple random  lottery, random number generator
 Systematic  random starting point, every third number

,  Stratified random sampling  used when you want different
groups in a population to be represented (divide group into
strata then pick randomly from both)
 Cluster sampling  used when you want to study groups that
are in regular contact with each other
 Multistage cluster sampling  divide into clusters then divide
into more clusters e.g. Schools, one high school, one class
o Non-probability Sampling = respondents selected based on
judgement of the researcher
 Convenience sampling
 Quota sampling  like stratified sampling but without a
sampling frame
 Snowball sampling  referrals, leads to distortions
 Purposive sampling  specific criteria of interest for study
- Sampling error = the degree to which the sample statistics differ from the
parameters of the population from which it was selected  avoided by
using probability sampling
True experiments
- Are experimental research designs that maximise internal validity and
enable us to test for causality
- Characteristics of true experiments:
o Manipulation  to ensure the cause proceeds the effect
o Comparison  to ensure the effect didn’t occur naturally
o Random assignment/randomization  ensures there are no other
explanations for the effect
- Manipulation
o When the researcher creates different level or conditions that
represent different values of the independent variable, while
keeping the external variables constant
o Manipulation check = used to assess how effective a manipulation
is
o Individual difference variables cannot be manipulated
- Randomization
o Provides a way of eliminating all possible systematic differences
between participants in different conditions at once
o Randomization failure = when there is an uneven distribution
o Statistical nuisance = the experimental group is not equal to the
control group
o Randomization check = measure relevant variables to see if
conditions are the same
- Elements of experimental designs
1. DV is manipulated into 2 groups (exp & con) + manipulation check
2. DV is measured in the 2 groups
3. Results are compared to see if they statistically differ
4. All other variables that can influence the IV & DV are controlled
- Random assignment = controlling for individual differences in
experimental conditions  when you have a large sample the biases will
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