Data for the VIBASS session on linear models. This is a simulated dataset that includes data about children. The variables in the dataset are:
data("Weights")An object of class "data.frame".
VIBASS Team.
age. Age (in years).
vegetables. Measure of vegetables consumption.
weight. Weight (in kg).
sex. Girl or Boy.
height. Height (in cm).
ethnicity Asian, Black or European.
data(Weights)
summary(Weights)
#> age vegetables weight sex height
#> Min. : 5.094 Min. :0.06729 Min. :10.95 Girl:48 Min. :124.3
#> 1st Qu.: 7.262 1st Qu.:0.16413 1st Qu.:17.03 Boy :52 1st Qu.:139.1
#> Median : 8.415 Median :0.21630 Median :19.44 Median :149.5
#> Mean : 8.625 Mean :0.22745 Mean :19.47 Mean :150.4
#> 3rd Qu.:10.370 3rd Qu.:0.28416 3rd Qu.:22.27 3rd Qu.:161.7
#> Max. :11.943 Max. :0.47274 Max. :27.54 Max. :177.4
#> ethnicity
#> Length:100
#> Class :character
#> Mode :character
#>
#>
#>
# ML estimates
lmW <- lm(weight ~ age, data = Weights)
summary(lmW)
#>
#> Call:
#> lm(formula = weight ~ age, data = Weights)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -5.2074 -1.4716 -0.2041 1.4890 4.3523
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 8.4838 1.0373 8.179 1.05e-12 ***
#> age 1.2735 0.1176 10.833 < 2e-16 ***
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 2.191 on 98 degrees of freedom
#> Multiple R-squared: 0.5449, Adjusted R-squared: 0.5403
#> F-statistic: 117.4 on 1 and 98 DF, p-value: < 2.2e-16
#>