An experiment was conducted to investigate the effects of procedural modifications on measurements of soil microbial biomass carbon, expressed as mg C per kg of soil. The study employed a 2 × 3 × 2 factorial design, testing two sieve sizes, three sample weights, and two shaking times, resulting in 12 distinct treatment combinations. Each combination was replicated four times in a completely randomized design. The response variable recorded was the amount of microbial carbon biomass (C). The purpose of the analysis is to quantify the main effects and possible interactions among sieve size, sample weight, and shaking time, as well as to determine whether any of the alternative procedures yield results within 10
Format
A data frame with 5 variables: DSample, Size, Weight, Time, C.
- DSample
Factor. Experimental unit identifier, representing the replicate number.
- Size
Factor. Sieve size used for processing soil samples ("Small" or "Large").
- Weight
Integer. Sample weight used in the protocol.
- Time
Integer. Duration in minutes of shaking during sample processing.
- C
Integer. Microbial biomass carbon in soil, measured as mg C per kg soil.
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
fit <- lm(C ~ Size * Weight * Time,
data = biomassc |>
transform(Weight = factor(Weight),
Time = factor(Time)))
anova(fit)
#> Analysis of Variance Table
#>
#> Response: C
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Size 1 80524 80524 17.1140 0.0002018 ***
#> Weight 2 12061 6030 1.2816 0.2899424
#> Time 1 179585 179585 38.1678 4.022e-07 ***
#> Size:Weight 2 10543 5272 1.1204 0.3372606
#> Size:Time 1 65 65 0.0139 0.9068521
#> Weight:Time 2 8855 4428 0.9410 0.3996224
#> Size:Weight:Time 2 5745 2872 0.6105 0.5486241
#> Residuals 36 169386 4705
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1