This is the issue. With only one observation per level of TypeBeat, it is not possible to fit this model. R is automatically dropping some of the predictors because with them, the matrix is singular.
To address, you might simulate some fake data to fit the models on.
library(tidyverse, quietly = TRUE)
#> Warning: package 'ggplot2' was built under R version 4.0.5
EX1HW5 <- tibble::tribble(
~TypeBeat, ~Course.Time.In.Hours, ~Score.A, ~Score.B, ~Score.C,
"upper.class", 5L, 34.4, 35.5, 39.2,
"middle.class", 10L, 30.2, 32.4, 34.7,
"inner.city", 15L, 20.1, 39.4, 54.3
)
EX1HW5 <- map_dfr(
list(EX1HW5) %>% rep(10),
mutate_if,
is.numeric,
~. + runif(length(.), min = -0.1, max = 0.1) # add random number
) %>%
arrange(TypeBeat)
EX1HW5
#> # A tibble: 30 x 5
#> TypeBeat Course.Time.In.Hours Score.A Score.B Score.C
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 inner.city 14.9 20.1 39.4 54.3
#> 2 inner.city 14.9 20.2 39.4 54.4
#> 3 inner.city 15.0 20.0 39.5 54.3
#> 4 inner.city 15.0 20.1 39.5 54.3
#> 5 inner.city 15.0 20.1 39.3 54.3
#> 6 inner.city 15.0 20.1 39.3 54.4
#> 7 inner.city 15.0 20.0 39.5 54.2
#> 8 inner.city 14.9 20.0 39.3 54.3
#> 9 inner.city 15.0 20.0 39.5 54.4
#> 10 inner.city 15.0 20.1 39.5 54.3
#> # ... with 20 more rows
Course <- aov(Course.Time.In.Hours ~ TypeBeat+Score.A + Score.B+Score.C, data = EX1HW5)
Course
#> Call:
#> aov(formula = Course.Time.In.Hours ~ TypeBeat + Score.A + Score.B +
#> Score.C, data = EX1HW5)
#>
#> Terms:
#> TypeBeat Score.A Score.B Score.C Residuals
#> Sum of Squares 498.9288 0.0026 0.0062 0.0016 0.0781
#> Deg. of Freedom 2 1 1 1 24
#>
#> Residual standard error: 0.05705951
#> Estimated effects may be unbalanced
Course.2<-aov(Course.Time.In.Hours ~ TypeBeat*Score.A+Score.B+Score.C, data = EX1HW5)
Course.2
#> Call:
#> aov(formula = Course.Time.In.Hours ~ TypeBeat * Score.A + Score.B +
#> Score.C, data = EX1HW5)
#>
#> Terms:
#> TypeBeat Score.A Score.B Score.C TypeBeat:Score.A Residuals
#> Sum of Squares 498.9288 0.0026 0.0062 0.0016 0.0069 0.0713
#> Deg. of Freedom 2 1 1 1 2 22
#>
#> Residual standard error: 0.05691599
#> Estimated effects may be unbalanced
Created on 2021-10-07 by the reprex package (v1.0.0)