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Unit of study_
ENVX1002: Introduction to Statistical Methods
2025 unit information
ENVX1002 is an introductory applied statistics and data science course tailored for students in the life and environmental sciences. It provides foundational skills essential for scientific careers and advanced studies in applied statistics and data science. Emphasizing critical and statistical thinking, the course is divided into three modules: exploring data, making decisions with data, and modelling data. Students will apply adaptive problem-solving skills to real-world issues in agriculture, biology, ecology, environmental science and health. Through interactive teaching methods and embedded technology, ENVX1002 enhances critical thinking and data-driven problem-solving in the natural sciences.
Unit details and rules
Managing faculty or University school:
Science
| Study level | Undergraduate |
|---|---|
| Academic unit | Life and Environmental Sciences Academic Operations |
| Credit points | 6 |
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Prerequisites:
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None |
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Corequisites:
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None |
| Prohibitions:
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ENVX1001 or MATH1005 or MATH1905 or MATH1015 or MATH1115 or DATA1001 or DATA1901 or BUSS1020 or STAT1021 or ECMT1010 |
| Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
- LO1. By the end of this course, students will be able to implement basic reproducible research practices—including consistent data organization, documented code, and version-controlled workflows—so that their statistical analyses and results can be readily replicated and validated by others.
- LO2. By the end of this course, students will demonstrate proficiency in utilizing R and Excel to effectively explore and describe life science datasets.
- LO3. By the end of this course, students will be able to apply parametric and non-parametric statistical inference methods to experimental and observational data using RStudio and effectively interpret and communicate the results in the context of the data.
- LO4. By the end ot this course, students will be able to put into practice both linear and non-linear models to describe relationships between variables using RStudio and Excel, demonstrating creativity in developing models that effectively represent complex data patterns.
- LO5. By the end of this course, students will be able to articulate statistical and modelling results clearly and convincingly in both written reports and oral presentations, working effectively as an individual and collaboratively in a team, showcasing the ability to convey complex information to varied audiences.
Unit availability
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Modes of attendance (MoA)
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