regression &corelation
A line that would appear if there were no real relationship.
By Chance Line
Total variability in the data.
Sum of Squares Total (SST)
Result from a t-test showing the size of the difference relative to variation.
t-statistic
The consistency of a measurement over time
Reliability
How well study conditions mirror real-world settings.
Ecological Validity
The difference between the observed and predicted values.
Residual
Variability explained by the model
Sum of Squares Regression (SSR)
Result from ANOVA showing variance explained by the model.
F-statistic
A numeric indicator of reliability (e.g., Cronbach’s alpha).
Reliability Coefficient
Consistency in identifying what to code.
Unitizing Reliability
The predicted value when all predictors are zero.
Intercept
Variability not explained by the model.
Sum of Squares Residual (SSE)
Correlation coefficient measuring relationship strength
r-statistic
How well items in a test measure the same concept.
Internal Consistency
Agreement in how content is classified or labeled.
Categorizing Reliability
A standardized regression coefficient.
Beta Weight =
Differences among repeated measures within the same participant.
Within-Subjects Variance –
Actual count in a dataset.
Observed Frequency
Confidence that the study demonstrates cause and effect.
Internal Validity
Agreement among coders on how content is interpreted.
Intercoder Reliability
The proportion of variance explained by the model.
Coefficient of Determination (R²)
Differences between individuals or groups.
Between-Subjects Variance
Theoretical count based on hypothesis.
Expected Frequency
Extent to which results generalize to other contexts
External Validity
A scale that measures agreement (e.g., strongly disagree to strongly agree)
Likert scale