Search Course Outline
Showing 25 course outlines from 3694 matches
2726
STATS 255
: Optimisation and Data-driven Decision Making2021 Semester One (1213)
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.
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 120 or 130 or 150 or 153 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
Restriction: ENGSCI 255
2727
STATS 255
: Optimisation and Data-driven Decision Making2020 Semester Two (1205)
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.
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 120 or 130 or 150 or 153 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
Restriction: ENGSCI 255
2728
STATS 255
: Optimisation and Data-driven Decision Making2020 Semester One (1203)
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.
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 120 or 130 or 150 or 153 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
Restriction: ENGSCI 255
2729
STATS 301
: Statistical Programming and Modelling using SAS2021 Semester Two (1215)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
Restriction: STATS 785
2730
STATS 301
: Statistical Programming and Modelling using SAS2021 Summer School (1210)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
Restriction: STATS 785
2731
STATS 301
: Statistical Programming and Modelling using SAS2020 Semester Two (1205)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
Restriction: STATS 785
2732
STATS 301
: Statistical Programming and Modelling using SAS2020 Summer School (1200)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
Restriction: STATS 785
2733
STATS 302
: Applied Multivariate Analysis2024 Semester One (1243)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
Restriction: STATS 767
2734
STATS 302
: Applied Multivariate Analysis2023 Semester One (1233)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
Restriction: STATS 767
2735
STATS 302
: Applied Multivariate Analysis2022 Semester One (1223)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
Restriction: STATS 767
2736
STATS 302
: Applied Multivariate Analysis2021 Semester One (1213)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
Restriction: STATS 767
2737
STATS 302
: Applied Multivariate Analysis2020 Semester One (1203)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
Restriction: STATS 767
2738
STATS 310
: Introduction to Statistical Inference2024 Semester One (1243)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
2739
STATS 310
: Introduction to Statistical Inference2023 Semester One (1233)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
2740
STATS 310
: Introduction to Statistical Inference2022 Semester One (1223)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
2741
STATS 310
: Introduction to Statistical Inference2021 Semester One (1213)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
2742
STATS 310
: Introduction to Statistical Inference2020 Semester One (1203)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
2743
STATS 313
: Advanced Topics in Probability2024 Semester Two (1245)
Characterisations of and relations between different kinds of random objects including random functions, random paths and random trees. Modes of convergence; the Law of Large Numbers and Central Limit Theorem.
Prerequisite: STATS 225
Restriction: STATS 710
Restriction: STATS 710
2744
STATS 313
: Advanced Topics in Probability2022 Semester Two (1225)
Characterisations of and relations between different kinds of random objects including random functions, random paths and random trees. Modes of convergence; the Law of Large Numbers and Central Limit Theorem.
Prerequisite: STATS 225
Restriction: STATS 710
Restriction: STATS 710
2745
STATS 320
: Applied Stochastic Modelling2024 Semester One (1243)
Construction, analysis and simulation of stochastic models, and optimisation problems associated with them. Poisson process, Markov chains, continuous-time Markov processes. Equilibrium distribution, reaching probabilities and times, transient behaviour. Use of R to simulate simple stochastic processes. Examples drawn from a range of applications including operations research, biology, and finance.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
2746
STATS 320
: Applied Stochastic Modelling2023 Semester One (1233)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
2747
STATS 320
: Applied Stochastic Modelling2022 Semester One (1223)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
2748
STATS 320
: Applied Stochastic Modelling2021 Semester One (1213)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
2749
STATS 320
: Applied Stochastic Modelling2020 Semester One (1203)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
2750
STATS 325
: Stochastic Processes2024 Semester Two (1245)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Prerequisite: B+ or higher in STATS 125 or B or higher in ENGSCI 314 or STATS 210 or 225 or 320, and 15 points from ENGSCI 211, MATHS 208, 250
Restriction: STATS 721
Restriction: STATS 721
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148