Analysis of Scientific Data (STAT1201)
Information valid for Semester 1, 2025
Course level
Undergraduate
Faculty
Schools
Biological Sciences School, History,Philos,Religion&Class, Info Tech & Elec Engineering, Mathematics & Physics School
Units
2
Duration
One Semester
Attendance mode
In Person
Class hours
3 Lecture hours
1 Tutorial hour
1 Practical or Laboratory hour
Incompatible
(EC134 or 135 or 136 or ECON1310 or 1320) or (HM236) or (ME203 or 204 or 206 or 207 or 214 or MS101 or 102 or 103 or 111 or 112 or 113 or 150 or 171 or 172 or 174 or 202 or 212 or 240 or 252 or 261 or 263) or (PY103 or 261 or 270 or 271 or 272) or (ZL211) or STAT2002 or 2201 or 2701 or LF209
Prerequisite
Year 12 Maths B or MT140 or MATH1040
Restricted
Not available to BE students
Assessment methods
Assignments & examinations
Course enquiries
Associate Professor Michael Bulmer (Summer Semester, Regular, St Lucia, In person)
Associate Professor Michael Bulmer (Semester 2, Regular, St Lucia, In person)
Doctor Ross McVinish (Semester 1, Regular, St Lucia, In person)
Doctor Vivi Arief (Semester 2, Regular, Gatton, In person)
Semester 1- Dr Ross McVinish
Semester 2 - Dr Michael Bulmer (St Lucia) and Dr Vivi Arief (Gatton)
Summer Semester - Dr Michael Bulmer
Study Abroad
This course is pre-approved for Study Abroad and Exchange students.
Current course offerings
Course offerings | Location | Mode | Course Profile |
Summer Semester, 2024 (25/11/2024 - 08/02/2025) | St Lucia | In Person | Course Profile |
Summer Semester, 2024 (25/11/2024 - 08/02/2025) | External | External | Course Profile |
Semester 1, 2025 (24/02/2025 - 21/06/2025) | Gatton | In Person | Course Profile |
Semester 1, 2025 (24/02/2025 - 21/06/2025) | St Lucia | In Person | Course Profile |
Semester 2, 2025 (28/07/2025 - 22/11/2025) | St Lucia | In Person | Profile unavailable |
Please Note: Course profiles marked as not available may still be in development.
Course description
Analysis of scientific data and experiments: Design of experiments and ethical research. Data modelling and management. Exploratory data analysis. Randomness and probability. Statistical analysis including linear regression, analysis of variance, logistic regression, categorical data analysis, and non-parametric methods.