Monty Leaman
Test por , creado hace más de 1 año

Statistical Analysis Exam

117
1
0
Monty Leaman
Creado por Monty Leaman hace casi 7 años
Cerrar

Research Methods: Multiple Regression

Research Methods: Multiple Regression

Pregunta 1 de 4

1

Fill in the Blank: Multiple Regression is a logical extension of linear regression that allows us to ... and assess whether adding additional variables or combination of variables (factors) to the regression will enhance the power of the regression model.

Selecciona una de las siguientes respuestas posibles:

  • examine the influence of a key X variable (regressor) on Y (dependent variable)

  • examine the influence of multiple X variables (regressors) on Y (dependent variable)

  • examine the influence of a key X variable (regressor) on Y (independent variable)

  • examine the influence of multiple X variables (regressors) on Y (independent variable)

Explicación

Pregunta 2 de 4

1

To carry out multiple regression, you must include ...

Selecciona una de las siguientes respuestas posibles:

  • three or more potentially useful predictors (variables)

  • all predictors (variables)

  • two or more potentially useful predictors (variables)

  • one or more potentially useful predictors (variables)

Explicación

Pregunta 3 de 4

1

What is factor analysis?

Selecciona una de las siguientes respuestas posibles:

  • A statistical method that describes the variability of observed variables, and correlates them to unobserved factors; usually in terms of a lower and higher score.

  • A statistical process by which all variables are forced into a regression model (all analysed at the same time) regardless of their statistical significance

Explicación

Pregunta 4 de 4

1

Which of the following is a statistical process by which all variables are forced into a regression model (all analysed at the same time) regardless of their statistical significance

Selecciona una de las siguientes respuestas posibles:

  • Simultaneous regression

  • Simple linear regression

  • Hierarchical regression

  • Logistic regression

Explicación

Anterior
Siguiente