Research Design Flashcards
Percentile Ranking
Percentage of scores in its frequency distribution that are equal to or lower than it.
Standard Error of Estimate
Measure of variation of an observation made around the computed regression line. “Used to check the accuracy of predictions.”
Standard Error of Measurement
A measure of how much measured test scores are spread around a “true” score.
Distribution Curve
A very common continuous probability distribution
Double-Blind Study
Experiment in which neither the participants nor the experimenters know who is receiving a particular treatment
Used to rule out bias.
Validity
The extent to which concepts, conclusion, or measurement is well-founded and likely corresponds accurately to the real world based on probability.
Reliability
The overall consistency of a measure.
A measured is said to have high reliability if it produces similar results under consistent circumstances.
Effect Size
A quantitative measure of the magnitude of a phenomenon.
Measurement of Central Tendency
A measure of central tendency is a single value that attempts to describe a set of data by identifying the central position within that set of data.
Mean: mathematical average
Median: Middle score of a data set that has been arranged in order of magnitude.
Mode: Most frequent score in a data set.
Range: Subtract the least value from the greatest value
Type 2 Errors
The failure to reject a false null hypothesis.
Type 1 Error
The rejection of a true null hypothesis
ANOVA’s
“Variation” among and in between groups
A collection of statistical models and their associated estimation procedures used to analyze difference between/among group means.
Types of Design: Meta-Analysis
Analysis that combines the results of multiple scientific studies
Types of Design: Review
Lit Review
Systematic Review
Types of Design: Experimental
Experiment with random assignment, often called true experimentation, use the scientific method to establish cause-effect relationship among a group of variables in a research study. Researchers make an effort to control for all variables except the one being manipulated (the independent variable). The effects of the independent variable on the dependent variable are collected and analyzed for a relationship.
Types of Research Design: Semi-Experimental
(often referred to as Causal-Comparative) seeks to establish a cause-effect relationship between two or more variables. The researcher does not assign groups and does not manipulate the independent variable. Control groups are identified and exposed to the variable. Results are compared with results from groups not exposed to the variable.
Example: field experiment
Type of research design: Correlational
explores the relationship between variables using statistical analyses. However, it does not look for cause and effect and therefore, is also mostly observational in terms of data collection.
Examples:
Case-control study
Observational Study
Types of Research Design: Descriptives
seeks to describe the current status of a variable or phenomenon. The researcher does not begin with a hypothesis, but typically develops one after the data is collected. Data collection is mostly observational in nature. Examples: Case-study Naturalistic Observation Survey
Confounding Variables
A variable that affects both the dependent and independent variable causing associations to appear that may not be valid. The confounding variable, if not planned for interfere with the relationship between the dependent and independent variable.
Independent Variables
A variable believed to affect the dependent variable.
Treatment or intervention variable, measured and manipulated.
Dependent variable
The variable the researcher is interested in.
Response variable, observed aspect of behavior of participant that has received an intervention.
Variables
Anything that has a quantity or quality that varies.
