Importing the data

farm <- read.csv("dataset.csv")

Question 1

Part a - Research Question (Rewritten):

Do adopters of rice-crayfish co-culture in the Hubei province differ from non-adopters in terms of the amount of cultivated land area used for their farming business?

Part b - Analysis of Research Question:

Factor of interest: adoption_behavior Response variable: land_area Variables: Adoption_behavior is categorical variable as it shows two groups - 1 = adpotor and 0 = non-adopter land_area is quantitative variable as it measures numerical value of an area of land used for farming.

Part c

To enable a more accurate comparison of adopters vs non-adopters, the data will first be cleaned by removing missing values before analysis. Both variable are already in suitable formats for an analysis, so no transformations will be performed.

Part d

To compare the distribution of land area among adopters and non-adopters, a boxplot will be made. This boxplot is suitable for this case, as it can compare quantitative variable (land_area) against categorical variable (adoption_behavior).

Question 2

library(ggplot2)

data <- read.csv("dataset.csv")

data_clean <- na.omit(data)

data_clean$adoption_behaviour <- factor(
  data_clean$adoption_behaviour,
  levels = c(0, 1),
  labels = c("Non-Adopter", "Adopter")
)

ggplot(data_clean, aes(x = adoption_behaviour, y = land_area)) +
  geom_boxplot() +
  labs(
    x = "Adoption Status",
    y = "Cultivated Land Area (mu)"
  ) +
  theme_minimal()

Figure 1. The distributions of cultivated land (mu) for adopters and non-adopters of rice-fish co-culture farming methods are displayed in Figure 1 for farmers in Hubei Province (China). The definition of total land area (mu) is that it comprises the total area of all land farmed (1 mu=667 m^2 of agricultural land). Each classification of adoption behaviour shows whether the farmer has adopted or not adopted rice-fish co-culture farming systems (1 = adopter; 0 = non-adopter). According to the boxplot representation of sampled data, boxplot data are constructed by plotting minimum, midrange, and maximum values for each sample, and by looking at how the two groups’ (adoption groups) values differ from one another based upon land area classification (total land area of each group).

AI use statement

I did not use generative AI tools for this assignment. All work was completed independently using course materials and my own understanding.