The interpolation forecast represents a forecast using the actual data from which the regression
equation was computed.
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True
False
As long as the residuals create a random pattern around the zero line in a residual plot,
the linear regression equation can be considered an appropriate fit to the data.
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True
False
When a linear equation is an appropriate model for a dataset, the distribution of data
around the regression line should suggest a series of
distributions centered on the regression line with constant
variance across the range of the chart.
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Rectangular
Skewed
Normal
Binomial
When the variability around the regression line is the same for all values of the
independent variable X this is referred to as .
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homoscedasticity
Interpolation variability
heteroscedasticity
quadratic variation
When an independent variable in a multiple regression model includes a value of X to
a higher power, such as X squared, and this model produces a higher value of R-
squared than a linear model, this suggests that the residual plot for the linear equation
did not produce a random pattern around the zero line of the residual plot.
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True
False
When testing for multicollinearity, a regression can be run in which one of the
suspected independent variables becomes the dependent variable and the other is the
,independent variable.
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True
False
A multiple regression model that has been shown to suffer from multicollinearity can
not be used even for predictive purposes.
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True
, False
Predictions when using a multiple regression equation can take which of the following
forms.
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Point estimate
Interval estimate
Neither of the above
Both of the above
Multicollinearity cannot occur in a simple linear regression model.
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True
False
The challenge in a DOE is to find the combination of
capable of producing an optimal response.
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output levels
experiments
fractional trials
factor levels
A four factor, two level design will require trials to explore the interaction
between factors.
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2
4
8
16
An OFAT does not fully cover the experimental design space.
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True
False
A design can cut the number of runs in a DOE without
loosing too much information.
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