PROBABILITY AND STATISTICS FOR DATA SCIENCE
STM4PSD
2021
Credit points: 15
Subject outline
This subject develops an understanding of probability and statistics applied to Data Science. Probability topics include joint and conditional probability, Bayes' Theorem and distributions such as the uniform, binomial, Poisson and normal distributions as well as properties of random variables and the Central Limit Theorem. Statistical inference and data analysis is also considered covering, among other topics, significance testing and confidence intervals with an introduction to methods such as ANOVA, linear and nonlinear regression and model verification. Applications to data science are considered and students will be exposed to the R statistical package as well as the mathematical type-setting package LaTeX.
SchoolEngineering and Mathematical Sciences
Credit points15
Subject Co-ordinatorMitra Jazayeri
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 4 - UG/Hons/1st Yr PG
Available as ElectiveYes
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
PrerequisitesN/A
Co-requisitesN/A
Incompatible subjectsSTM4PM OR STA4SS
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsThis subject will be offered to sufficient enrolment numbers
Minimum credit point requirementN/A
Assumed knowledgeN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
Select to view your study options…
Melbourne (Bundoora), 2021, Semester 1, Blended
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorMitra Jazayeri
Class requirements
Computer LaboratoryWeek: 10 - 22
One 2.00 hours computer laboratory per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Unscheduled Online ClassWeek: 10 - 22
One 2.00 hours unscheduled online class per week on any day including weekend during the day from week 10 to week 22 and delivered via online.
Pre-recorded Lecture
Assessments
Assessment element | Category | Contribution | Hurdle | % | ILO* |
---|---|---|---|---|---|
Four written assignments (500-words equivalent each, 2,000-words total)Calculations and associated written discussion and conclusions. | N/A | N/A | No | 40 | SILO1, SILO2, SILO3, SILO4, SILO5, SILO6 |
3 hour final exam (3000-words equivalent)Following release of results, papers can be reviewed in accordance with University policy. | N/A | N/A | No | 60 | SILO1, SILO2, SILO3, SILO4, SILO5, SILO6 |
Melbourne (Bundoora), 2021, Semester 2, Blended
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorMitra Jazayeri
Class requirements
Computer LaboratoryWeek: 30 - 42
One 2.00 hours computer laboratory per week on weekdays during the day from week 30 to week 42 and delivered via face-to-face.
Scheduled Online ClassWeek: 30 - 42
One 2.00 hours scheduled online class per week on any day including weekend during the day from week 30 to week 42 and delivered via online.
Pre-recorded Lecture
Assessments
Assessment element | Category | Contribution | Hurdle | % | ILO* |
---|---|---|---|---|---|
Four written assignments (500-words equivalent each, 2,000-words total)Calculations and associated written discussion and conclusions. | N/A | N/A | No | 40 | SILO1, SILO2, SILO3, SILO4, SILO5, SILO6 |
3 hour final exam (3000-words equivalent)Following release of results, papers can be reviewed in accordance with University policy. | N/A | N/A | No | 60 | SILO1, SILO2, SILO3, SILO4, SILO5, SILO6 |