Suppose you want to create a model where "parking duration" depends on "building area", "number of floors" as well as "height". How do you do that in R?

We use the same lm() function but this time the formula is as follows

model <- lm(parking_duration ~ building_area + number_of_floors + height)

If we find summary of our model using following

summary(model)

The output is as follows

Call:

lm(formula = parking_duration ~ building_area + number_of_floors +

    height)

Residuals:

    Min      1Q  Median      3Q     Max

-378.02 -190.79  -47.92  219.22  419.39

Coefficients: (1 not defined because of singularities)

                   Estimate Std. Error t value Pr(>|t|)   

(Intercept)      1708.99539  476.27213   3.588  0.00155 **

building_area      -0.03149    0.02297  -1.371  0.18358   

number_of_floors   -0.12384    4.77416  -0.026  0.97953   

height                   NA         NA      NA       NA   

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 234.6 on 23 degrees of freedom

Multiple R-squared:  0.08213, Adjusted R-squared:  0.002317

F-statistic: 1.029 on 2 and 23 DF,  p-value: 0.3732

We can see that none of the coefficients are statistically significant.