BackPrediction Intervals definitions
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1/15BackSkip to main contentBackPrediction Interval
Range estimating a single y value from regression, reflecting uncertainty and incorporating both model and individual variability. Confidence Interval
Range estimating a population parameter, expressing certainty about where the true value lies based on sample data. Regression Line
Equation modeling the relationship between x and y, used to predict y values for given x values. Point Estimate
Best guess for a predicted y value, calculated by plugging a specific x into the regression equation. Critical Value
Number from the t-distribution determining the width of the interval, based on confidence level and degrees of freedom. Standard Error
Measure of variability in predicted y values, calculated from sample data and used in margin of error. Margin of Error
Amount added and subtracted from the point estimate to form the interval, combining critical value and standard error. Degrees of Freedom
Value used in t-distribution calculations, typically equal to sample size minus two in regression contexts. Linear Correlation
Strength and direction of the relationship between x and y, verified before constructing intervals. Sample Size
Number of x-y pairs in the dataset, affecting calculations for standard error and margin of error. t-Distribution
Probability distribution used for critical values when sample sizes are small or population variance is unknown. x Bar
Mean of the x values in the sample, used in margin of error calculations for prediction intervals. Sigma x
Sum of x values, or sometimes standard deviation of x, used in statistical calculations for regression. Sigma x Squared
Sum of squared x values, a statistic used in margin of error formulas for prediction intervals. Upper Bound
Highest value in the prediction interval, found by adding margin of error to the point estimate.
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