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Research methods exam 2
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Terms in this set (39)
construct
A hypothetical factor that cannot be observed directly but is inferred from certain behavior and assumed to follow from certain circumstances. (relates to operational definitions)
reliability
The extent to which measures of the same phenomenon are consistent and repeatable.
Results from a minimum amount of measurement error
Produced by a factor that introduces inaccuracies into the measurement of a variable.
Validity
Measures what it is designed to measure
Content validity (not face validity)
Criterion
(predicting)
Nominal Scales
Assign numbers to events to classify them into one group or another
Numbers are used as names [categorical]
Used to:
assign individuals to categories
count the number of individuals falling into each category (reported as frequencies)
Ordinal Scales
Numbers are used to indicate rank order
Used to:
rank order (1st, 2nd, 3rd, etc.) individuals based on one or several other pieces of data
Interval Scales
scores indicate quantities
equal intervals between scores
score of zero is just a point on the continuum
a score of zero does not indicate 'absence' of something
Used to:
calculate score from participants' responses on a test
Ratio Scales
scores indicate quantities
equal intervals between scores
score of zero does denote 'absence' of something
Used to:
calculate score from participants' responses on a test
central tendency
What scores are at the center of a distribution.
Descriptive statistics: Measures of variability
How spread out or dispersed scores are in a distribution.
Range
The difference between the high and low scores of a group.
Standard deviation
An estimate of the average amount by which the scores in the sample deviate from the mean score.
Variance
standard deviation squared
Interquartile range
The range of scores between the bottom 25% and the top 25% of scores.
Statistical Analysis: Visual displays of data
Histograms from frequency distributions
With graphs, carefully examine Y-axis to avoid being misled
Statistical Analysis: Inferential Statistics
Inferring general conclusions about the population from sample data.
Null hypothesis
No relationship ("no difference") between variables in the population expected, given the sample.
H0
Alternative Hypothesis
A relationship ("a difference") between variables in the population is expected, given the sample.
H1
Effect size
Emphasizes the size of difference between variables, not merely whether there is a difference
Confidence intervals
Range within which population mean likely to be found.
Power
Chance of rejecting a false null hypothesis.
Experiment
A systematic research study in which the investigator directly varies some factor (or factors), holds all other factors constant, and observes the results of the variation.
Independent variable
The factor of interest to the experimenter, the one being studied to see if it will influence behavior.
Manipulated variable
Situational
Features in the environment that participants might encounter. (mirror when taking candy)
task
Changes in the types of tasks participants perform.
Instructional
Telling different groups of participants to complete a particular task in different ways.
Extraneous variable
The factor that is held constant.
confound
Any uncontrolled extraneous variable that covaries with the independent variable and could provide an alternative explanation of the results.
dependent variable
Describes behaviors that are measured outcomes of experiments
ceiling effects
the task is too easy, all scores are very high, differences are disguised
floor effects
the task is too difficult, all scores are very low, differences are disguised.
Subject Variables
A personal characteristic on which individuals vary from one another. They already exist in participants when they enter a study.
e.g., Gender, age, race
Natural-groups design
A researcher measures a subject variable, forms different groups based on people's level of that variable, and then measures how the different groups respond on other variables.
Statistical conclusion validity
Proper statistical analyses and conclusions
Construct validity
Well-chosen and well-defined IVs and DVs
External validity
The degree to which research findings generalize beyond the experimental context.
Externally valid studies generalize to other...
1. populations
2. environments
3. times
internal validity
The degree to which the experiment is methodologically sound and confound-free.
Does my study actually answer the research question I proposed and designed to answer?
Internally valid studies have...
1. Valid operational defintions.
2. valid measurements.
3. no confounds.
Subject Selection
Occurs when groups are not equivalent
Attrition
Occurs when participants do not complete the study.
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