Research Design Flashcards
Variables
- Independent
- Dependent
- Confounding
- Quasi-Independent
Independent Variable
o Manipulated by the researcher (it’s the presumed agent of change)
Dependent Variable
o Measured by the researcher (determines if IV has an effect)
Confounding Variable
o Reduces internal validity (this variable is an extraneous variable. It varies systematically with the IV)
Quai-Independent Variable
o An experiment that uses existing groups (rather than random assignment) to determine condition
Types of Designs
Correlational
Descriptive
Experimental
Correlational Design
How are these variables related?
a type of research design where a researcher seeks to understand what kind of relationships naturally occurring variables have with one another. In simple terms, correlational research seeks to figure out if two or more variables are related and, if so, in what way
Descriptive Design
a scientific method which involves observing and describing the behavior of a subject without influencing it in any way.
Experimental Design
What is the effect of the IV on the phenomenon?
how participants are allocated to the different conditions (or IV levels) in an experiment
ANOVAs
Analysis of variance is a statistical test to determine if all sample groups in a study are affected by the same factors, and if they are affected to the same degree. The groups are kept separate and tests are done independently on each group, but the results are then compared. The sample groups are examined to see if the average within each group is the same and how much impact different variables have on the test.
Type I Error
False positive – reject null hypothesis but it is true
Type II Error
(miss) do not reject null when there is a real effect
Measures of central tendency
• (mean, median, and mode) are statistics that describe the center of a data set. The mean tells us the average value or score; the median tells us the midpoint in the range of values; and the mode tells us the most common value in the data set.
Effect Size
- the size of a relationship between two variables.
- Sometimes effect size is known as treatment effect because it is often used when dealing with therapeutic interventions (ie., this treatment is shown to be more effective than another at treating a specific disorder).
Reliability
- the extent to which a test or other instrument is consistent in its measures.
- For example, a weight scale can be judged reliable if measures for a 25-pound weight do not vary over time or change for subsequent weightings.
- Reliability is an important concept in science. If a test is not reliable, we cannot find the answers to our questions.
Validity
- If the test does indeed measure what it is intended to measure, then we can say that the test is valid (or has validity).
- tests are usually judged according to their validity and their reliability (if the test produces similar results each time the test is taken).
- Tests that are valid are also reliable
- a test might be reliable without it being valid.
Double-blind Study
- is one in which neither the participants nor the experimenters know who is receiving a particular treatment.
- This procedure is utilized to prevent bias in research results. Double-blind studies are particularly useful for preventing bias due to demand characteristics or the placebo effect.
Distribution Curve
- shows how often an experiment will produce a particular result
- The curve is symmetricaland bell shaped, showing that trials will usually give a result near the average, but will occasionally deviate by large amount
- The width of the “bell” indicates how much confidence one can have in the result of an experiment — the narrower the bell, the higher the confidence.
Standard Error of Estimate
• the measure of variation of an observation made around the computed regression line. Simply, it is used to check the accuracy of predictions made with the regression line.
Standard Error of Measurement
• estimates how repeated measures of a person on the same instrument tend to be distributed around his or her “true” score. The true score is always an unknown because no measure can be constructed that provides a perfect reflection of the true score
Percentile Ranks
• The percentile rank of a score is the percentage of scores in its frequency distribution that are equal to or lower than it. For example, a test score that is greater than 75% of the scores of people taking the test is said to be at the 75th percentile, where 75 is the percentile rank.
