BA

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Given the above data what is the correlation coefficient if the R^2 is 0.69.

-0.83

Based on the ANOVA table what is the Rsquare of the regression?

.667

Based on the coefficients table how many predictor variables are not significiant?

1

If a categorical independent variable contains three categories, then _________ dummy variable(s) will be needed to uniquely represent these categories.

2

What is the VIF for a variable that has an Rsquared of 0.67 when regressed upon by the other predictor variables?

3

What percentage of observations are within one standard error of the estimated values?

68%

What is the alternate hypothesis of the F-test in the regression model?

At least one coefficient is not equal to zero.

Given the correlation matrix what can a researcher conclude about displacement and horsepower?

Displacement horsepower are directly related.

A strong linear relationship between X and Y indicates that X causes Y.

False

The proportion of variability in the dependent variable that is explained by the independent variable is called multiple R.

False

If one way ANOVA is performed on a factor and it is insignificant what should be used to create a forecast?

Group Means*** Perform a regression instead****

What does the scatter plot show?

Heteroscedastity

Based on the Scatter plot above how would transform the variables X and Y to make it more linear? Using Tukey's Ladder of Powers and the Bulge Rule

Increase X and/or Decrease Y**** Increase X and/or Increase Y***

What measures the strength of the linear relationship between the dependent and the independent variable?

Multiple R

The above Normal Probability plot is giving evidence of

Non-Normally distributed residuals.

What is a type I error?

Null hypothesis is true but rejected

Excessively complex models suffer from ____________ and have poor predictive power.

Overfitting

What is not required to for the estimator to be BLUE?

Random Sampling****

What measure tells the accuracy of a model?

Rsquared

Why do we like to fix multicollinearity in our data?

So we can make inference in regression.

The standard deviation is to the mean as the ____________ is to the regression line.

Standard error

A regression diagnostic tool used to study the possible presence of multicollinearity is

The correlation matrix

What is b0 in the regression equation?

The value of the outcome when all predictors are 0.

A dummy variable is used as an independent variable in a regression model when

The variable is categorical.

A violation of this regression assumption can cause coefficients to be unstable?

There is a linear relationship among any of the independent variables in the model.

If r = -1, then we can conclude that there is a perfect relationship between X and Y.

True

Ordinary Least Squares is very sensitive to outliers.

True

Plotting values of X against corresponding residuals is a method for determining the linearity of X-Y data.

True

True or False : The likelihood of an Rsquare that high by chance is approximately zero!

True

True or False: The residual is the difference between the observed value of the dependent variable and the predicted value of the dependent variable.

True

True or false: Backward Elimination is used to prune variables from a model.

True

True or false: Coefficients on dummy variables represent the effect of the group vs a reference group.

True

True or false: In the multiple regression model, the goodness-of-fit measure R-squared always increases or remains the same when an additional explanatory variable is added

True

What does it mean to say there is error in our regression?

We cannot predict Y perfectly.

Given the data above using what transformation might be appropriate?

X^3*** y^2***

The line described by the regression equation attempts to

minimize the squared distance from the points

When two or more of the explanatory variables are highly correlated, this situation is referred to as

multicollinearity

Given the correlation matrix what variable is most linearly related to MPG?

Weight


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