T3 Slide W2 Flashcards
What is the basic start for research
- Noting an interesting question
- Stating the question in such a way that it can be answered
- Undergoing the scientific method
Experimental Group
The group in an experiment that is exposed to the Independent Variable
Control Group
The group in an experiment that is not exposed to an Independent Variable but is neutral
Non Experimental Research
- Describe relationships between variables
- Cannot test cause-and-effect relationships
- Descriptive
- Historical
- Correlational
- Qualitative
Descriptive Research
- Describes characteristics of existing phenomena
- Provides a broad picture
- Serves as a basis for other types of research
Historical Research
- Describes past events in the context of other past or current events
- Primary and secondary sources of data
Correlational Research
- Asks what several events have in common
- Asks whether knowing one event can allow prediction of another event
- Does not imply causation
Qualitative Research
- Examines behaviour in natural social, cultural, and political contexts
- Usually results in non-quantitative data
Qualitative Research
- Examines behaviour in natural social, cultural, and political contexts
- Usually results in non-quantitative data
Types of Experimental Research
- True Experiment
- Quasi-Experiment
True Experiment
- Participants assigned to groups
- Treatment variable is controlled by researcher
- Control of potential causes of behaviour
Quasi-Experiment
- Participants are preassigned to groups
- Useful when researcher cannot manipulate variables
Types of Research Design Table
See booklet
Variables
- Variables lie at the heart of psychological research
- Psychological research is all about exploring the nature of the relationship among variables
What is a Variable?
- an entity that can be measured
- can take on different measured variables eg: height, weight, income
- the more precise the measurement the more useful the measurement is.
What is the difference between a variable and a value
- A value is a subset of a Variable
- Variables can have different values
Independent Variables
A variable that forms groups or conditions in the study
What is an Independent Variable?
- A variable that forms groups or conditions in the study
- It is the condition that is compared in a study
Independent Variables
- can be directly or indirectly manipulated by researcher
- controlled by the researcher
Independent Variable - Direct Manipulation
When a researcher directly controls the IV
eg: administer a drug
Independent Variable - Indirect Manipulation
- where groups are naturally occuring such as in a gender difference study
- IV does not require manipulation to measure differences
When Independent Variables need to be divided into levels.
- Levels are the different groups of an IV in a study
- IV:gender - Lev els:
- male
- female
- intersex
- IV:gender - Lev els:
What makes a good Independent Variable?
- The Independent Variable is not confounded
- Levels do not vary systematically with other variables
- Dependent variable is sensitive to changes in the independent Variable
What makes a good Independent Variable?
- The Independent Variable is not confounded
- Levels do not vary systematically with other variables
- Dependent variable is sensitive to changes in the independent Variable
Dependent Variables
- The outcome, performance or condition being assessed
- Called dependent because its scores depend on the treatment condition or experimenter manipulation
- Needs to be operationlised
Control Variable
Variable whose influence you want to control
Extraneous Variables
Confounding occurs when an extraneous variable:
- Varies systematically across the levels of the independent variable
- Is correlated with the dependent variable
Confounding Variable
- An Extraneous variable that makes it impossible to draw casual relationships from the data as changes in the DV could be caused by the IV or confounding variable
How to control for influence?
Can be done by design or analysis
Mediator Variables
Thought to describe the psychological process that occurs to create the relationship
Moderator Variables
Variables change the strength of an effect or relationship between two variables
Summary - Dependent Variable
A variable that is measured to see whether the treatment or manipulation of the independent variable had an effect
AKA:
- Outcome variable
- Results variable
- Criterion variable
Summary - Independent Variable
A variable that is manipulated to examine its impact on a dependent variable
AKA:
- Treatment
- Factor
- Predictor Variable
Summary - Control
A variable that is related to the dependent variable, the influence of which needs to be removed
AKA:
- Restricting Variable
Summary - Extraneous Variable
- A variable that is related to the dependent variable or independent variable that is not part of the experiment - Threatening Variable
Summary - Moderator
A variable that is related to the dependent variable or independent variable and has an impact on the dependent variable
AKA:
- Interacting Variable
Between Subjects Design
- Also known as independent samples.
- Each subject is exposed to one level of each Independent Variable
Within Subjects Design
- Also known as repeat measures design
- Each subject is exposed to all levels of each independent variable
Hypothesis
- an if, then statement in objective form
- is testable
- posits relationship between factors
- Data are collected to confirm or refute
- are testable but not provable
What is a Hypothesis?
- a brief statement that declares the outcome of a study
- Describes relationship between variables
- Makes a prediction of outcome posed as a priori
What is a priori?
- used to distinguish two types of knowledge, justifications or arguments.
- A priori knowledge or justification is independent of experience (for example ‘All bachelors are unmarried’);
- Claim to support a fact but actually not supported by factual study.
Essential features of a Hypothesis? (4)
- Is Breif
- Written in past tense
- A statement not a question
- States expected relationship between variables.
Falsification
- The process where something can be demonstrated to be false.
- A hypothesis is declarative that can be falsified or rejected
- Contrast between showing something is false with showing something is true.
Why is falsification important?
- Helps to create certainty important to Popper’s philosophy
- Hypotheses and theories are refined through falsification
- Develops strength and credibility if they are not able to be falsified
The Null Hypothesis
- A statement of no difference/relationship/effect.
- The starting point for evaluating a research study
- The evaluation process assumes the null to be true
- We then collect evidence to break down the null
Null Hypothesis Formula
Ho: µ1 = µ2
The null hypothesis is always that there is no difference between groups with respect to means,
The Research Hypothesis
A statement that says something is going on
there is a relationship or effect that shows difference
can be non-directional
when we pose a hypothesis in our research we posit an alternative hypothesis
H1: µ1 ≠ µ2
- A statement that says something is going on
- there is a relationship or effect that shows difference
- can be non-directional
- when we pose a hypothesis in our research we posit an alternative hypothesis
H1: µ1 ≠ µ2
H1: µ1 ≠ µ2
- A hypothesis or alternate hypothesis
- The Null Hypothesis has been falsified
- Indicates that there is a relationship/effect/difference between the variables.
Population
- A collection of units
- can be large or narrow
- generally infer about a general population
What is a Sample Population?
- A smaller collection of observations from a population
- Used to infer characteristics about the population
- the bigger the sample it is more likely to reflect the larger population
- results may vary from sample to sample but will be similar on averages
- we generalise our results tto the greater population using Estimation and Inference
Descriptive Statistics
Aim to capture the essential features of the results in an easily comprehensible form.
Statistical Significance
- Is the result statistically significant or are the results by chance?
- do the Statistical results support or fail to support our hypothesis
- are the samples an accurate reflection of the whole populaiton?
What is p value
- A hypothesis test that is used to determine the significance of the results from a study.
- The probability that the results from an experiment or study are due to chance and not the experimental conditions
- Also known as calculated probability
Null Hypothesis Significance Testing
- The most used method for testing research questions with statistics
- Fisher and the Lady Tasting Tea
- Fisher claims that we should calculate the probability of an event and then evaluate this within a research context
- p value tells us about probability not meaningfulness
Critical Appraisal of published literature
- Don’t get too attached to your idea as you may need to change it.
- Don’t pick a trivial project
- Don’t try to do more than is possible
- Try to do something new
Critical Appraisal - What it IS
- A balanced assessment
- Assessment of both process and results
- Considers quantitative and qualitative dimensions
- Undertaken by all health practitioners
Critical Appraisal - What it IS NOT
- Dismissal of research
- Narrow critique of results
- Based solely on statistical analysis
- Only for experts
Two Skills of Critical Appraisal
- Searching the Literature
- Critically appraising the literature that exists
Two purposes for literature review
- Discover what has already been done in your area of interest
- Chronological representation of ideas
- Shows which ideas have been abandoned due to lack of support
- Shows which ideas have been confirmed as “truths”
- Discover what needs to be done in your area of interest
Process of review for Journals (6)
- Researcher submits article in format specified by the Journal
- Editor distributes article to 3 Reviewers
- → peer review + blind review
- FOUR possible recommendations
- Accept outright
- Accept with revisions
- Reject with suggestions for revision
- Reject outright
- Editor conveys decision to author
- Average rejection rate is >80%
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