These datasets were created to help you practice core statistical tools in the context of simple, but biologically inspired situations. Each one is small enough to explore manually, rich enough to generate meaningful results, and designed to match the methods you’ll encounter in your research life.
You’re comparing two groups of organisms—perhaps plants given
different light conditions or animals fed different diets. You want to
know: did the treatment really change growth? Use this for
t-tests (1-sample and 2-sample) and permutation tests. -
group (Control/Treatment), value
(growth/weight/etc.) - Download
t_test_data.csv
This dataset captures the frequency of different color morphs across
habitats. Does the environment affect which morph dominates? Classic
chi-square question. - environment, morph,
count - Download
chi_sq_data.csv
Animals were randomly assigned one of three drug treatments, and
their behavioral response was measured. ANOVA time: do the means differ?
Use for one-way ANOVA with post-hoc testing. - drug
(DrugA/B/C), response (e.g., reaction time) - Download anova_oneway.csv
This time, you’re exploring the effect of both treatment and sex on a
biological response. Was there an interaction? Use this for two-way
ANOVA. - treatment, sex, response
- Download anova_twoway.csv
Fifteen individuals measured at three time points. Maybe it’s a
training study or developmental time course—either way, the same animals
were measured repeatedly. Use this for repeated measures ANOVA or mixed
models. - subject, time (T1/T2/T3),
response - Download
repeated_measures.csv
Wing length vs body mass in insects. Are longer wings associated with
heavier bodies? A simple and interpretable dataset for correlation and
scatterplots. - wing_length_mm, body_mass_g -
Download cor_data.csv
You’re studying what predicts reproductive output—mass, age,
treatment? A great dataset for linear regression with both continuous
and categorical predictors. - fecundity,
mass_g, age_years, treatment - Download reg_data.csv
Did the treatment improve survival? This binary outcome dataset
models survival (yes/no) based on mass and treatment, ideal for logistic
regression. - survival (0/1), mass_g,
treatment (0/1) - Download
glm_binomial.csv
How many eggs did an animal lay, depending on food availability and
exposure? Count data + log-transformed exposure = Poisson/GLM
playground. - eggs_count, food_index,
exposure_offset_log - Download glm_poisson.csv
This dataset tracks how long individual birds take to feed across
multiple trials under different treatments. Repeated measures nested in
individuals—perfect for mixed-effects models. - subject,
trial, treatment, latency_sec -
Download mixed_data.csv
Two groups measured on a skewed biological trait—maybe hormone levels
or infection burden. Use this to practice non-parametric tests like
Wilcoxon and Kruskal-Wallis. - group (A/B),
value - Download
np_data.csv
Six traits measured on three species of plants or animals. This is
your go-to for dimensionality reduction with PCA or MDS. What’s the
hidden structure? - species, trait1 through
trait6 - Download
multi_trait_data.csv
Measurements of petal and sepal dimensions in 3 iris species. Classic for clustering, classification, and ANOVA.
data(iris)
head(iris)Eruption durations and waiting times between eruptions at Old Faithful in Yellowstone. Great for learning about distributions.
data(faithful)
head(faithful)Miles per gallon, horsepower, number of cylinders, and more. Perfect for regression, correlation, and plotting practice.
data(mtcars)
head(mtcars)Paired design study on how two drugs affect sleep in 10 patients. Use it for paired t-tests and boxplots.
data(sleep)
head(sleep)Tooth length of guinea pigs given Vitamin C via orange juice or supplements. Great for comparing groups and effect sizes.
data(ToothGrowth)
head(ToothGrowth)Weight gain of baby chicks on different diets. A go-to for repeated measures and visualizing growth curves.
data(ChickWeight)
head(ChickWeight)data()