The _______________ for multiple linear regression do not have constant variance.
sample residuals
The ______________ for multiple linear regression have constant variance.
error terms
QQPlot and histogram are used to assess what in MLR?
normality
Residuals vs predictor ar...
The _______________ for multiple linear regression do not have constant
variance. - ANSWER- sample residuals
The ______________ for multiple linear regression have constant variance. -
ANSWER- error terms
QQPlot and histogram are used to assess what in MLR? - ANSWER- normality
Residuals vs predictor are used to predict what in MLR - ANSWER- linearity
Residuals vs fitted values are used to assess what in MLR - ANSWER- constant
variance and independence
Points that are far from the mean of the x's are called - ANSWER- leverage points
Points that are far from the mean of the x's and y's are called - ANSWER-
Influential points
It is good practice to perform regression analysis with and without what? -
ANSWER- outliers
What is used to quantify outliers? - ANSWER- Cook's distance
How much all the values in the model change when the ith value is removed is
known as what? - ANSWER- Cook's distance
Cooks distance that should be investigated. - ANSWER- D_i > 4/n or D_i > 1 or
Large D
The proportion of variability in Y than can be explained by the predictor variables.
- ANSWER- R-Squared
, Model variables used to account for selection bias. - ANSWER- Controlling
factors
Continuous variables are converted to ________ when there is a distinct gap in a
variable distribution. - ANSWER- Indicator variable
The number of degrees of freedom for a T test for the statistical significance of a
MLR coefficient? - ANSWER- n-p-1
When the regression model has a high F value/low p-value. - ANSWER- At least
one variable has explainitory power on the response variable.
When testing subsets of coefficients using anova command. - ANSWER- order
matters
When can "year" be used as a qualitative variable? - ANSWER- If the variable is
not very granular
Used to evaluate the relationship between any two qualitative variables. -
ANSWER- Pearson Chi-squared test
A command needed prior to running a pearson chi-squared test of qualitative
variables. - ANSWER- table
What should you do when you have a high number of predicting variables due to
a large number of categorical variables resulting in numerous dummy variables. -
ANSWER- Reduce the dummy variables into groups
Which category does R choose as the baseline label when creating dummy
variables with as.factor() - ANSWER- The first
If you use a model without an intercept, how will interpreting coefficients be
different? - ANSWER- No baseline for comparison
The statistical significance of a predicting variable in a marginal and conditional
models are _____________ . - ANSWER- independent
No analysis of prediction is complete without evaluating the performance of the
model using this technique. - ANSWER- cross validation
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