Research and Program Development Flashcards
(66 cards)
Dependent Variable
The variable that is (HOPEFULLY) changed based on your experiment, the outcome variable
Independent Variable
What is controlled, utilized, given in the experiement
Parsimony and Occam’s Razor
Interpreting results in the simplest way
Confounding/Flawed Research
Multiple testing (seeing multiple counselors, receiving multiple treatments) that is not controlled for in the experiment)
Basic Research
Advances our theory
Applied Research
Advances our practices
Control group
Does not receive the experimental treatment, no exposure to the independent variable
Hypothesis Testing
Developing an experiment in order to explore a hunch or idea developed by R. A. Fisher
Null Hypothesis
States that the treatment or IV will not have an affect
Alternative Hypothesis
States that the treatment or IV does affect the outcome of the experiement
Between Subjects Design
Different subjects get exposure or lack of exposure to different things
In Subjects Design
One pool of subjects receive or don’t receive the treatment (pre-test post-test design)
Parameter
Property that defines a sample (age, sex, etc.)
Probability
The likelihood that something will happen, also known as significance level, P for our field is generally .05 but can range from .000 to .01 and still be considered significant
findings or not due to chance, P can be translated into a percentage that describes the portion of the sample whose results were achieved by chance (i.e. .05 = 5% of the sample’s scores were obtained by chance – not your experimental design)
Type I Error or Alpha Error
Rejecting the null when it is true (saying there is significance in your treatment when there isn’t), increasing P levels will reduce this error, increasing sample size will reduce this error
Type II Error or Beta Error
Accepting the null when it is not true (saying there isn’t significance in your treatment when there is), increasing sample size will reduce this error, increasing P will increase the chance of this error
T Test
Used for two samples to compare means, you obtain a single t score and compare it to the critical t value based on the sample size and your significance level and if the t value you found is greater than the critical t you have significance
F Statistic
Used for more than two groups, represents and ANOVA test, same process used as with the t test
Two Way ANOVA or MANOVA
Used for more than two groups and more than one IV
Correlation
Represents a relationship between two variables, ranges from -1.00 to 1.00, the closer to -1 or 1 the stronger the relationship, can have negative correlation or positive, a score close to 0 represents no or low correlation, strong correlation does not imply causality
Baseline Measure
Testing before any IV has been performed
Single-Blind Study
Either the researchers or the participants (but not both) are unaware of what group each represents
Double-Blind Study
Neither the researchers nor subjects know what category or group they belong to
Normal Curve
Bell shaped, mean, median, and mode all fall on the same line, 68% of scores fall in -1 to +1 standard deviation, 95% fall within -2 to +2 standard deviations, 99.7% fall into -3 to +3 standard deviations
