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Showing 25 course outlines from 4473 matches

3276

STATS 210

: Statistical Theory
2021 Semester Two (1215)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125 Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
3277

STATS 210

: Statistical Theory
2021 Semester One (1213)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125 Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
3278

STATS 210

: Statistical Theory
2021 Summer School (1210)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125 Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
3279

STATS 210

: Statistical Theory
2020 Semester Two (1205)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing. This course is a prerequisite for the BSc(Hons) and masters degree in statistics.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125 Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
3280

STATS 210

: Statistical Theory
2020 Semester One (1203)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing. This course is a prerequisite for the BSc(Hons) and masters degree in statistics.
Subject: Statistics
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125 Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
3281

STATS 220

: Data Technologies
2025 Semester One (1253)
Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.
Subject: Statistics
Prerequisite: 15 points at Stage I in Computer Science or Statistics
3282

STATS 220

: Data Technologies
2024 Semester One (1243)
Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.
Subject: Statistics
Prerequisite: 15 points at Stage I in Computer Science or Statistics
3283

STATS 220

: Data Technologies
2023 Semester One (1233)
Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.
Subject: Statistics
Prerequisite: 15 points at Stage I in Computer Science or Statistics
3284

STATS 220

: Data Technologies
2022 Semester One (1223)
Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.
Subject: Statistics
Prerequisite: 15 points at Stage I in Computer Science or Statistics
3285

STATS 220

: Data Technologies
2021 Semester One (1213)
Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.
Subject: Statistics
Prerequisite: 15 points at Stage I in Computer Science or Statistics
3286

STATS 220

: Data Technologies
2020 Semester One (1203)
Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.
Subject: Statistics
Prerequisite: 15 points at Stage I in Computer Science or Statistics
3287

STATS 225

: Probability: Theory and Applications
2025 Semester One (1253)
Covers the fundamentals of probability through theory, methods, and applications. Topics should include the classical limit theorems of probability and statistics known as the laws of large numbers and central limit theorem, conditional expectation as a random variable, the use of generating function techniques, and key properties of some fundamental stochastic models such as random walks, branching processes and Poisson point processes.
Subject: Statistics
Prerequisite: B+ or higher in ENGGEN 150 or ENGSCI 111 or STATS 125, or a B+ or higher in MATHS 120 and 130 Corequisite: 15 points from ENGSCI 211, MATHS 208, 250
3288

STATS 225

: Probability: Theory and Applications
2024 Semester One (1243)
Covers the fundamentals of probability through theory, methods, and applications. Topics should include the classical limit theorems of probability and statistics known as the laws of large numbers and central limit theorem, conditional expectation as a random variable, the use of generating function techniques, and key properties of some fundamental stochastic models such as random walks, branching processes and Poisson point processes.
Subject: Statistics
Prerequisite: B+ or higher in ENGGEN 150 or ENGSCI 111 or STATS 125, or a B+ or higher in MATHS 120 and 130 Corequisite: 15 points from ENGSCI 211, MATHS 208, 250
3289

STATS 225

: Probability: Theory and Applications
2023 Semester One (1233)
Covers the fundamentals of probability through theory, methods, and applications. Topics should include the classical limit theorems of probability and statistics known as the laws of large numbers and central limit theorem, conditional expectation as a random variable, the use of generating function techniques, and key properties of some fundamental stochastic models such as random walks, branching processes and Poisson point processes.
Subject: Statistics
Prerequisite: B+ or higher in ENGGEN 150 or ENGSCI 111 or STATS 125, or a B+ or higher in MATHS 120 and 130 Corequisite: 15 points from ENGSCI 211, MATHS 208, 250
3290

STATS 225

: Probability: Theory and Applications
2022 Semester One (1223)
Covers the fundamentals of probability through theory, methods, and applications. Topics should include the classical limit theorems of probability and statistics known as the laws of large numbers and central limit theorem, conditional expectation as a random variable, the use of generating function techniques, and key properties of some fundamental stochastic models such as random walks, branching processes and Poisson point processes.
Subject: Statistics
Prerequisite: B+ or higher in ENGGEN 150 or ENGSCI 111 or STATS 125, or a B+ or higher in MATHS 120 and 130 Corequisite: 15 points from ENGSCI 211, MATHS 208, 250
3291

STATS 225

: Probability: Theory and Applications
2021 Semester One (1213)
Covers the fundamentals of probability through theory, methods, and applications. Topics should include the classical limit theorems of probability and statistics known as the laws of large numbers and central limit theorem, conditional expectation as a random variable, the use of generating function techniques, and key properties of some fundamental stochastic models such as random walks, branching processes and Poisson point processes.
Subject: Statistics
Prerequisite: B+ or higher in ENGGEN 150 or ENGSCI 111 or STATS 125, or a B+ or higher in MATHS 120 and 130 Corequisite: 15 points from ENGSCI 211, MATHS 208, 250
3292

STATS 225

: Probability: Theory and Applications
2020 Semester One (1203)
Covers the fundamentals of probability through theory, methods, and applications. Topics should include the classical limit theorems of probability and statistics known as the laws of large numbers and central limit theorem, conditional expectation as a random variable, the use of generating function techniques, and key properties of some fundamental stochastic models such as random walks, branching processes and Poisson point processes.
Subject: Statistics
Prerequisite: 15 points from ENGGEN 150, ENGSCI 111, STATS 125 with a B+ or higher, or MATHS 120 and 130 with a B+ or higher Corequisite: 15 points from MATHS 250, ENGSCI 211 or equivalent
3293

STATS 240

: Design and Structured Data
2025 Semester Two (1255)
An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.
Subject: Statistics
Prerequisite: STATS 101 or 108
Restriction: STATS 340
3294

STATS 240

: Design and Structured Data
2024 Semester Two (1245)
An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.
Subject: Statistics
Prerequisite: STATS 101 or 108
Restriction: STATS 340
3295

STATS 240

: Design and Structured Data
2023 Semester Two (1235)
An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.
Subject: Statistics
Prerequisite: STATS 101 or 108
Restriction: STATS 340
3296

STATS 240

: Design and Structured Data
2022 Semester Two (1225)
An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.
Subject: Statistics
Prerequisite: STATS 101 or 108
Restriction: STATS 340
3297

STATS 240

: Design and Structured Data
2021 Semester Two (1215)
An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.
Subject: Statistics
Prerequisite: STATS 101 or 108
Restriction: STATS 340
3298

STATS 240

: Design and Structured Data
2020 Semester Two (1205)
An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.
Subject: Statistics
Prerequisite: STATS 101 or 108
Restriction: STATS 340
3299

STATS 255

: Optimisation and Data-driven Decision Making
2025 Semester One (1253)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 108 or 120 or 130 or 162 or 199 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
3300

STATS 255

: Optimisation and Data-driven Decision Making
2024 Semester One (1243)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 108 or 120 or 130 or 162 or 199 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255