| Tag | Value |
|---|---|
| file | Inferential_Statistics_eur-inferential_statistics-126-en_eur-inferential_statistics-126-en |
| name | eur-inferential_statistics-126-en |
| section | Inferential Statistics/Regression/R squared, Inferential Statistics/Regression/Prediction |
| type | num |
| solution | 0.006 |
| tolerance | 0 |
| Type | Performing analysis |
| Program | SPSS |
| Language | English |
| Level | Statistical Literacy |
A researcher is interested in the consequences of the financial crisis for 16- and 17-year olds. She wants to predict their leisure expenses in November 2012 [expenses_nov] from a number of predictors. She collected data from 202 teenagers: 1) leisure expenses in November 2012 [expenses_nov]; 2) leisure expenses in July 2012 [expenses_jul]; 3) income from their side occupation in November 2012 [salary_nov]; 4) time spent on studying [studytime]; and 5) their educational level [education] (1 = vmbo, 2 = havo, 3 = vwo)*.
**translation for the Dutch education levels: (1 = Lower General Secondary Education, 2 = Higher General Secondary Education, 3 = Pre-university Education)*
Open the data file.
How much did the proportion of explained variance in leisure expenses in November 2012 [expenses_nov] increase after the variable educational level [education] was added as a predictor to the model?
The explained variance increased with 0.006.