Tag | Value |
---|---|
file | Inferential_Statistics_uu-Standardized-coefficient-809-en_uu-Standardized-coefficient-809-en |
name | uu-Standardized-coefficient-809-en |
section | Inferential Statistics/Regression/Standardized coefficient |
type | schoice |
solution | TRUE, FALSE, FALSE, FALSE |
Type | Interpretating output |
Program | SPSS |
Language | English |
Level | Statistical Literacy |
The hourly wage of teachers (SALERY PER HOUR) can be predicted with a multiple regression model from the number of years of experience a teacher has (EXPERIENCE) and how well the teacher is perceived (QUALITY). The quality of the teacher is the average peer rating. The SPSS output of the regression analysis is shown.
Which of the two variables, EXPERIENCE or QUALITY, is the most important predictor of SALARY PER HOUR and why?
To determine which variable is the most significant predictor, 3 aspects can be looked at: - p-value: a more significant predictor is more important than a less significant predictor. A smaller p-value means more significance (because of this, C is erroneous, because wrong-sum). - t-value: a higher t-value means the predictor is more significant. This option is not among the answer options. - Beta: standardized regression coefficients are given here. A higher beta means a more important predictor. This leads to the correct answer: A. Both regression coefficient (B) and standard error (Std. Error) cannot be used to locate the most significant predictor without additional information about the scales.