STAT1005 (v.1) Introduction to Probability and Data Analysis
| Area: | School of Elec Eng, Comp and Math Sci (EECMS) |
|---|---|
| Credits: | 25.0 |
| Contact Hours: | 3.0 |
| TUITION PATTERNS: | The tuition pattern provides details of the types of classes and their duration. This is to be used as a guide only. Precise information is included in the unit outline. |
| Lecture: | 1 x 2 Hours Weekly |
| Computer Laboratory: | 1 x 1 Hours Weekly |
| Workshop: | 1 x 1 Hours Weekly |
| Anti Requisite(s): |
STAT1001 (v.1)
Statistical Probability
or any previous version
AND STAT1002 (v.1) Statistical Data Analysis or any previous version |
| UNIT REFERENCES, TEXTS, OUTCOMES AND ASSESSMENT DETAILS: | The most up-to-date information about unit references, texts and outcomes, will be provided in the unit outline. |
| Syllabus: | This unit is an introduction to methods of statistical analysis and their role in scientific inference - drawing conclusions about the world using data. It begins with an introduction to probability, which provides a foundation for understanding randomness, uncertainty, chance, and most important of all, for statistical inference. We start with a gentle introduction to definitions of probability and probability models, and then go on to discuss probability distributions, and tools and techniques that can be used to model a wide range of phenomena, as well as those that are useful in statistical inference. In the second part of the unit, we discuss descriptive statistics and inferential statistics. Throughout, we will emphasize that how data are collected determines the nature of the conclusions that we are entitled to draw from any study. Students will be introduced to the R language statistical environment, which they will use for exploring, displaying, and analysing data, and for carrying out and reporting the results of statistical inference. |
| Field of Education: | 010103 Statistics |
| Result Type: | Grade/Mark |
Availability
| Year | Location | Period | Internal | Partially Online Internal | Fully Online |
|---|---|---|---|---|---|
| 2021 | Bentley Perth Campus | Semester 1 | Y | ||
| 2021 | Bentley Perth Campus | Semester 2 | Y | ||
| 2021 | Dubai Intern'l Academic City | Trimester 2 | Y | ||
| 2021 | Dubai Intern'l Academic City | Trimester 3 | Y | ||
| 2021 | Dubai Intern'l Academic City | Trimester 3 | Y | ||
| 2021 | Miri Sarawak Campus | Semester 1 | Y |
Partially Online Internal refers to some (a portion of) learning provided by interacting with or downloading pre-packaged material from the Internet but with regular and ongoing participation with a face-to-face component retained. Excludes partially online internal course/units run through the Curtin Bentley-based Distance Education Area which remain Central External
Fully Online refers to the main (larger portion of) mode of learning provided via Internet interaction (including the downloading of pre-packaged material on the Internet). Excludes online course/units run through the Curtin Bentley-based Distance Education Area which remain Central External
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