In this experiment, four relative concentrations of calcium (A = 1, B = 5, C = 10, D = 20) were each applied to five individual plants, with treatments assigned in a completely randomized design across 20 pots. After the experimental period, the total root length (in centimeters) of each plant was measured. The resulting dataset includes both the root length measurements and a set of dummy variables representing the levels of the Calcium treatment factor. This structure facilitates statistical analysis of the effects of different calcium concentrations on plant root growth.
Format
A data frame with 7 variables: Pot, Calcium, Length, d1, d2, d3, d4.
- Pot
Factor. Unique identifier for each pot (experimental unit).
- Calcium
Factor. Calcium treatment group for each pot, with levels "A" = 1, "B" = 5, "C" = 10, "D" = 20.
- Length
Integer. Total root length (in centimeters) measured for each pot at the end of the experiment.
- d1
Integer. Dummy variable indicating membership in calcium level "A" (1 if Calcium = "A", 0 otherwise).
- d2
Integer. Dummy variable indicating membership in calcium level "B" (1 if Calcium = "B", 0 otherwise).
- d3
Integer. Dummy variable indicating membership in calcium level "C" (1 if Calcium = "C", 0 otherwise).
- d4
Integer. Dummy variable indicating membership in calcium level "D" (1 if Calcium = "D", 0 otherwise).
Source
Welham, S. J., Gezan, S. A., Clark, S. J., and Mead, A. (2015) Statistical Methods in Biology: Design and analysis of experiments and regression
Examples
anova(lm(Length ~ 1 + d2 + d3 + d4, data = calcium2))
#> Analysis of Variance Table
#>
#> Response: Length
#> Df Sum Sq Mean Sq F value Pr(>F)
#> d2 1 1066.82 1066.82 13.9727 0.001793 **
#> d3 1 512.53 512.53 6.7129 0.019700 *
#> d4 1 883.60 883.60 11.5730 0.003645 **
#> Residuals 16 1221.60 76.35
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1