BCB744 Biostatistics Exam Rubric (2025)
General Structure of the Rubric
Each Task is evaluated under the following axes:
- Technical Accuracy (50%)
- Depth of Analysis (20%)
- Clarity and Communication (20%)
- Critical Thinking (10%)
Each subcomponent is marked on a 0–100 scale, then scaled to its proportion of the task weight. For example, Task 5 is worth 30% of the total mark, so a sub-question like 5.1 (one of five) may contribute up to 6% if evenly weighted.
Task 1: Initial Processing [10%]
Weight within task:
- 1.1 Extraction and Restructuring (50%)
- 1.2 Conversion and Summarisation (50%)
Rubric:
- Technical Accuracy (50%)
- Correct unpacking of NetCDF variables (names, dimensionality): 15%
- Time conversion handled correctly (POSIX timestamps): 10%
- Data reshaped into appropriate long format: 15%
- Presence of appropriate columns (year, quarter, etc.): 10%
- Depth of Analysis (20%)
- Efficient use of methods (e.g. hyper_tibble() or expand.grid() vs brute loops): 10%
- Use of Cartesian indexing or equivalent vectorised operation: 10%
- Clarity and Communication (20%)
- Code is readable, well-commented: 10%
- Summary of the resulting data structure shown and interpretable: 10%
- Critical Thinking (10%)
- Indicates understanding of spatial × temporal structure and mentions NA implications: 10%
Task 2: Exploratory Data Analysis [10%]
2.1 Weighted Mean Time Series
- Weighted mean across time: 15%
- Time series for 100 pixels: 15%
2.2 Summary Statistics:
- Descriptive stats: 20%
- Visualisations: 20%
- Interpretation: 20%
2.3 Observation Density Map: 10%
Rubric:
- Technical Accuracy (50%)
- Proper handling of weights and NA filtering: 10%
- Correct aggregation logic (quarter, pixel, etc.): 10%
- Appropriateness of visualisation syntax and ggplot conventions: 10%
- Use of statistical descriptors (mean, sd, skew, etc.) correctly: 10%
- Map projection/geodesic coordinates and section overlay accuracy: 10%
- Depth of Analysis (20%)
- Commentary on skewness, kurtosis, and statistical implications: 10%
- Recognition of seasonal/temporal signals in plots and stats: 10%
- Clarity and Communication (20%)
- Plot labels, axes, titles intelligible and precise: 10%
- Logical narrative supporting visualisations/statistics: 10%
- Critical Thinking (10%)
- Justification of metric choices, handling of anomalous years: 5%
- Suggestions of ecological explanations (e.g., photoperiod, storminess): 5%
Task 3: Inferential Statistics I [20%]
Weight within task:
- Hypotheses: 10%
- Model selection and justification: 20%
- Assumption testing: 20%
- Result interpretation and diagnostics: 50%
Rubric:
- Technical Accuracy (50%)
- Correct use of linear model and specification (additive, no interaction): 20%
- Explicit assumptions tested (normality, homogeneity): 10%
- Proper model diagnostics and visual checks: 10%
- Use of correct significance thresholds and p-value interpretation: 10%
- Depth of Analysis (20%)
- Justification for using aggregate means vs raw data: 10%
- Consideration of alternative models (e.g., GAMs): 10%
- Clarity and Communication (20%)
- Hypotheses stated cleanly, concisely: 10%
- Figure/Table references integrated smoothly in the narrative: 10%
- Critical Thinking (10%)
- Recognition of model limitations and implications (e.g. low R²): 10%
Task 4: Spatial Assignment [10%]
4.1 Section Assignment: 5%
4.2 Bioregion Assignment: 5%
Rubric:
- Technical Accuracy (50%)
- Correct application of Haversine formula or great-circle logic: 20%
- Accurate section_id assignment: 10%
- Bioregion mapping via join or merge: 10%
- Correct data columns preserved/renamed: 10%
- Depth of Analysis (20%)
- Efficiency of matching routine (e.g., mapply() or vectorised join): 10%
- Consideration of spatial boundaries (e.g., limiting to section 1–22): 10%
- Clarity and Communication (20%)
- Annotated code, explanation of proximity logic: 10%
- Output (head(), summary(), tail()) shows assignment integrity: 10%
- Critical Thinking (10%)
- Considers effect of section resolution or mapping error: 10%
Task 5: Inferential Statistics II [30%]
Each sub-task contributes approximately 6% unless reweighted explicitly.
Rubric per sub-task (5.1–5.5):
- Technical Accuracy (50%)
- Model type (ANOVA, LM, ANCOVA) appropriate: 15%
- Correct test execution (summary, diagnostics): 15%
- Assumptions evaluated, violations addressed: 10%
- Non-parametric alternative proposed when appropriate: 10%
- Depth of Analysis (20%)
- Explicit rationale for model choice: 10%
- Discussion of structure in data (nesting, lack of interaction): 10%
- Clarity and Communication (20%)
- Hypotheses clearly and formally stated: 10%
- Visualisations appropriately labelled and explained: 10%
- Critical Thinking (10%)
- Insight into ecological implications of findings (e.g., BMP trend): 10%
Add 1–2 bonus marks if:
- Multicollinearity (e.g., VIF) or autocorrelation (e.g., DW test) is discussed
- Advanced diagnostics (e.g., Breusch–Pagan, TukeyHSD) are used correctly
Task 6: Write-up [10%]
Rubric:
- Technical Accuracy (50%)
- Consistent reference to previous results, correct figure/table interpretation: 25%
- Accurate paraphrasing of statistical results: 15%
- Adherence to 2-page length limit, integration of material: 10%
- Depth of Analysis (20%)
- Rich synthesis across Tasks 2–5, not isolated repetition: 10%
- Conceptual connection of seasonality, trend, and spatial heterogeneity: 10%
- Clarity and Communication (20%)
- Coherent scientific writing style, flowing paragraph structure: 10%
- Effective integration of figure references and literature: 10%
- Critical Thinking (10%)
- Limitations clearly acknowledged and reflected on: 5%
- Forward-looking ecological insight or recommendation offered: 5%
Reuse
Citation
@online{smit,_a._j.2025,
author = {Smit, A. J.,},
title = {BCB744 {Biostatistics} {Exam} {Rubric} (2025)},
date = {2025-05-31},
url = {http://tangledbank.netlify.app/BCB744/assessments/BCB744_Prac_Exam_Rubric_2025.html},
langid = {en}
}