An experiment was conducted to examine the effects of soil type and water availability on the growth of lupin plants grown individually in pots. To control for possible gradients due to temperature and light, the pots were arranged in a square grid and a Latin square design was used, treating rows and columnsas crossed blocking factors. Treatments followed a 2 × 2 factorial structure, combining two soil types (Soil: clay [C] or sand [S]) and two water supply levels (Water: low [L] or high [H]). Each treatment combination was applied to a group of pots. Plant height (cm) was recorded for each pot at the end of the experiment, allowing assessment of both main and interaction effects of soil type and water availability on lupin growth.
Format
A data frame with 7 variables: ID, Row, Column, Treatment, Water, Soil, Height.
- ID
Factor. Unique identifier for each pot (experimental unit).
- Row
Factor. Row position of the pot in the Latin Square grid.
- Column
Factor. Column position of the pot in the Latin Square grid.
- Treatment
Factor. Combined treatment label for soil type and water supply (e.g., "CH", "CL", "SH", "SL").
- Water
Factor. Water supply level applied to the pot: "L" (low) or "H" (high).
- Soil
Factor. Soil type: "C" (clay) or "S" (sand).
- Height
Numeric. Height (in centimeters) of the lupin plant at the end of the experiment.
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
I. Shield, Rothamsted Research.
Examples
anova(lm(Height ~ Row + Column + Treatment, data = lupin))
#> Analysis of Variance Table
#>
#> Response: Height
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Row 3 6.162 2.0540 3.165 0.1068420
#> Column 3 74.912 24.9706 38.478 0.0002589 ***
#> Treatment 3 24.662 8.2206 12.667 0.0052542 **
#> Residuals 6 3.894 0.6490
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1