Question

If your computer printout includes an F-statistic and p-value for the overall model,how should you interpret the p-value?

Accepted Answer

A) the probability that all of the coefficients are actually equal to zero 
B) the probability that all of the coefficients other than the intercept are actually zero and we would observe the estimated results 
C) the probability that the model is completely invalid 
D) the probability that the model is incorrectly specified 
A) the probability that all of the coefficients are actually equal to zero 
B) the probability that all of the coefficients other than the intercept are actually zero and we would observe the estimated results 
C) the probability that the model is completely invalid 
D) the probability that the model is incorrectly specified

If your computer printout includes an F-statistic and p-value for the overall model,how should you interpret the p-value?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

Prediction, Goodness-Of-Fit and Modeling Issues

The Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Regression With Time Series Data: Stationary Variables

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters

Exam 8: Further Inference in the Multiple Regression Model

If your computer printout includes an F-statistic and p-value for the overall model,how should you interpret the p-value?

An Introduction to Econometrics

Pp : Prob, Probability Primer, Probability Primer

The Simple Linear Regression Model

Interval Estimation and Hypothesis Testing

Prediction, Goodness-Of-Fit and Modeling Issues

The Multiple Regression Model

Using Indicator Variables

Heteroskedasticity

Regression With Time Series Data: Stationary Variables

Random Regressors and Moment Based Estimation

Simultaneous Equations Models

Regression With Time Series Data: Nonstationary Variables

Vector Error Correction and Vector Autoregressive Models

Time-Varying Volatility and Arch Models

Panel Data Models

Qualitative and Limited Dependent Variable Models

Filters