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Unit 2 (Chapters 6 - 9) Vocab
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Terms in this set (21)
Linear Model
An equation of a line that represents reality
PREDICTED VALUE
Found by using a linear model and substituting in an x-value to predict y.
RESIDUALS
Observed value - predicted value
SLOPE
"y-units per x-unit"
INTERCEPT
Gives a starting point in y-units. The y-value when x =0
R-SQUARED
Gives the fraction (percent) of the variability of y accounted for by the change in x.
DOES THE PLOT THICKEN? CONDITION
The scatterplot or residuals plot should show a consistent spread.
LINEAR REGRESSION CONDITIONS TO CHECK
Quantitative Variables, Straight Enough, Outliers, Does the Plot Thicken
SCATTERPLOTS
Shows the relationship between 2 quantitative variables
DESCRIBING ASSOCIATION OF SCATTERPLOT
Discuss the direction, form, strength, possible outliers, and context of a scatter plot
DESCRIBING DIRECTION
Positive or negative (slope of the line)
DESCRIBING FORM
Linear, Curved, Exotic, or no pattern
DESCRIBING STRENGTH
The closeness of the points
OUTLIER
A point that does not fit the overall pattern
RESPONSE VARIABLE
The y-values
EXPLANATORY VARIABLE
The x-values
CORRELATION COEFFICIENT
A numerical value that describes the direction and strength of a linear association
EXTRAPOLATION
When it is unsafe to make predictions for x far from the ones used to find the linear model
LEVERAGE
Data points whose x-values are far from the mean of x
INFLUENTIAL POINT
If the point is removed from the data set and a very different slope is produced
LURKING VARIABLE
A variable that is not explicitly part of a model but affects the way the variables in the model appear to be related.
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