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Showing 25 course outlines from 3701 matches

2701

STATS 210

: Statistical Theory
2023 Semester One (1233)
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
2702

STATS 210

: Statistical Theory
2023 Summer School (1230)
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
2703

STATS 210

: Statistical Theory
2022 Semester Two (1225)
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
2704

STATS 210

: Statistical Theory
2022 Semester One (1223)
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
2705

STATS 210

: Statistical Theory
2022 Summer School (1220)
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
2706

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
2707

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
2708

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
2709

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
2710

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
2711

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
2712

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
2713

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
2714

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
2715

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
2716

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
2717

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
2718

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
2719

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
2720

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
2721

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
2722

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
2723

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
2724

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
2725

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