Deneme Sınavı Soruları

It aims to provide a more robust and accurate estimate of the model’s error compared to traditional methods.

To obtain the CV estimate of variance, the residuals are computed for each fold of the CV process.

The residuals in the CV process capture the discrepancies between the model’s predictions and the actual observations.

The CV estimate of variance is calculated by taking the highest value of the squared residuals across all folds and dividing it by the degrees of freedom.

The CV estimate of variance provides a more realistic assessment of the model’s predictive accuracy.

There are fewer extreme values on the higher end of the data.

The left tail of the distribution is extended.

There are lower extreme values in the first stage of the data.

There isn’t any extreme value in the distribution of the data.

The right tail of the distribution is extended.

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Adjusted R² penalizes the additional of more regressors.

R² serves a superior measure compared to adjusted R².

R² is introduced to counterbalance the act of adding regressors solely to boost the adjusted R² value.

The value of dependent variable must be higher in the R² compared to adjusted R².

The value of R² is higher than value of adjusted R².

It is the sample of univariate regression function.

It is the sample of bivariate regression model with the intercept term.

It is the sample of univariate regression function with the intercept term.

It is the sample of bivariate regression model without the intercept term.

It is the quadratic regression model with the intercept term.

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A lower R² indicates a better fit.

R² is defined as higher than 1.

R² can’t decrease when additional variables are added to the model.

It contains the rate of total sum of squares to residual sum of squares.

More variables don’t increase R².

A restaurant might want to assess the
effectiveness of its recent advertising
campaign in boosting sales.

Macroeconomists may seek to evaluate the
efficacy of various government policies.

Developing new social relationships.

Almost every business might want to know
how their profits change as they expand.

Both government and private experts
should be interested in the price and
income elasticity of demand.

The model has one dependent variable

The model has one independent variable

The model has one dependent variable and one independent variable

The model has no variable

The model has one sample and one observation variable

Homoscedasticity or equal variance of ui . All error terms have to have the same variance, technically, var(ui |Xi ) = σ2.

Zero average (mean) value of error term ui . Technically, the conditional mean value of ui is zero, E(ui |Xi ) = 0.

Autocorrelation or serial correlation between the disturbances.

The number of observations n must be greater than the number of parameters to be estimated.

Zero covariance between ui and Xi . There should not be a relation between these two terms.