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Learn how to conduct psychological research
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1) Intuition: process of coming to direct knowledge or certainty without reasoning or inferring; forming hypotheses
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2) Authority: acceptance of facts stated by authorities; used in designing stage; expert whose facts are subject to testing using the scientific process
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3) Rationalism: uses reasoning to arrive at knowledge, assumes that valid knowledge is acquired if correct reasoning process is used; identify the outcomes that indicate the truth/falsity of the hypotheses
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4) Empiricism: acquire knowledge through experiences; cognition and perception; empirical observations to be conducted under controlled conditions
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2) Reality in nature: our experiences are real; forms basis for further research; scientists assume that there is an underlying reality that they are trying to uncover
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3) Discoverability: it is possible to discover the regularities and reality; must assume that we can discover laws that make experiences real
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1) Uniformity/regularity in nature
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Conceptualisation
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adopting a scientific approach; definition of terms
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Operationalisation
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construct vs measure; working definition of the construct - specification
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Hypothesis
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forming a testable hypothesis; science is falsifiable; embracing the null; can never be proven to be correct
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Research study
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experimental vs non-experimental
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Data collection
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how do we treat subjects? measurement modes used
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Data analysis
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samples and sample sizes; comparing group scores
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Presentation
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presenting research findings
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Nominal
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categories, non-quantitative, uses symbols to classify variable values
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Ordinal
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rank-order scale of measurement; cannot assume equidistance
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Interval
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equal intervals, no absolute zero point (arbitrary)
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Ratio
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absolute zero point, rank-ordering, equal intervals
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Quant. exp. research designs
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Conducting experiments to establish causations by manipulating IVs and observing changes on DVs
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Levels of the IV and manipulation strength
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>2 levels of the IV to conclude causality
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Strength: levels of the IV must be distinct and different from each other
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# of IVs?
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>1 IV!!
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Having only one -> misleading
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In experimental designs
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They can be continuous or categorical in nature
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Number of DVs
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There can be alternatives! -> accuracy/response time
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In experimental designs
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EV
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CV
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- Might compete with the IV in explaining the outcome
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- An EV that may eliminate the ability to claim that the IV causes changes in the DV
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- Affects absolute outcome but not experimental outcome
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- Creeps in systematically and affects one level of the IV but not the other
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Between (goes through 1 level of the IV)
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Within (goes through all levels of the IV)
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Shorter time to obtain results
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Elimination of CVs
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Random assign. could cause unequal groups of unequal abilities (confounding)
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Mental fatigue, floor effects
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Between
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Within: counter-balancing to counter sequencing effects (order effects and carryover effects)
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- matching: alt. method to/can be combined with randomisation
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- randomised: possibility that there is a sequence that has a higher frequency of a certain variable
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- randomisation
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- intrasubject: does not solve order effects
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- complete: N!, N = # of levels of IV; may not have enough participants
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- incomplete: multiple sequences, control order effects, N sequences, only works for even #; odd # – create a mirror!
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Experimental
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Non-experimental
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manipulated the IV (variability)
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did not manipulate the IV (variability due to individual differences
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can infer causality
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can only infer correlation
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control over EVs
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construct and use good test items
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1. Match the research objectives.
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2. Appropriate for the respondents to be surveyed.
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3. Short, simple questions.
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4. Avoid loaded or leading questions
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5. Avoid double-barrelled questions
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6. Avoid double negatives
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7. Determine whether closed-ended, or open-ended, or mixed format questions are needed
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8. Construct mutually exclusive and exhaustive response categories for closed-ended questions
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9. Consider the different types of closed-ended response categories (measurement modes) – would an interval scale or ordinal scale be more useful?
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10. Use multiple items to measure complex or abstract constructs
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11. Make sure questionnaire is easy to use; - Limit contingency questions (redirection) - Control response bias (social desirability) - Control response bias (response set) – insert contrasting items
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12. Pilot-test – think-aloud technique
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Mean
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Variability
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- Wanting to know how the scores spread around the mean
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- Presence of outliers can be misleading
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Standard deviation: describing the spread of a group of scores; average amount that scores differ from the mean
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Variance
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1. Converting raw scores to Z-scores
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2. Converting Z-scores to raw scores
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- Number of SDs a score is above or below the mean
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X=(Z)(SD)+M
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Z=(X-M)/SD
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Distribution of Z-scores: M=1,SD=1
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Ceiling effect
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when an IV no longer has an effect on the DV
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Floor effect
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when a data-gathering instrument has a lower limit to the data values it can reliably specify
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Cheatography n. The art of mapping complex subjects into clear, instantly navigable reference guides.
