Course Title: Statistics and Measurement Analysis
Part A: Course Overview
Course Title: Statistics and Measurement Analysis
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
GEOM2162 |
City Campus |
Undergraduate |
171H School of Science |
Face-to-Face |
Sem 2 2020, Sem 1 2021, Sem 1 2023 |
Course Coordinator: Dr Safoora Zaminpardaz
Course Coordinator Phone: +61399252307
Course Coordinator Email: safoora.zaminpardaz@rmit.edu.au
Course Coordinator Availability: By appointment, by email
Pre-requisite Courses and Assumed Knowledge and Capabilities
Assumed Knowledge
The knowledge associated with a passing grade in first year mathematics (MATH2211 or MATH2163 or equivalent) is assumed.
Course Description
This course is a second-year core component of the BH116 Bachelor of Applied Science (Surveying) (Honours) and BH117 Bachelor of Science (Geospatial Science) (Honours) programs. It establishes knowledge of the basic concepts in statistics and the analysis of surveying & geospatial data for later courses in the BH116 & BH117 programs.
The Statistics section provides a broad introductory knowledge of statistical methods in data analysis, with an emphasis on techniques that are useful in Geospatial science.
The Measurement Analysis section covers the application of least squares adjustment to generate statistically optimal results from measurement data and to assess measurement quality.
Objectives/Learning Outcomes/Capability Development
This course contributes to the following Program Learning Outcomes for BH116 Bachelor of Applied Science (Surveying)(Honours) and BH117 Bachelor of Applied Science (Geospatial Science)(Honours)
1.1 Describe the fundamental and applied scientific knowledge that underpins Surveying and Geospatial Science.
1.2 Demonstrate in-depth understanding of the spatial models and mathematical methods used in contemporary practice.
1.3 Understand specialist bodies of knowledge in Surveying and Geospatial Science
2.1 Apply standard and advanced techniques to solve a range of measurement and data management problems.
3.1 Design and implement solutions to complex problems in survey measurement and land development.
3.2 Interpret and critically analyse results and make informed judgements on the appropriateness of solutions.
3.3 Apply critical and analytical skills in a scientific and professional manner.
4.1 Communicate effectively by means of oral, written and graphical presentations to peers and a wider audience.
6.3 Professionally manage and use information.
Upon successful completion of this course, you will be able to:
- Describe the nature of random variables and probability distributions through direct calculation and computer simulation
- Perform statistical inference tasks using software (descriptive statics, t-test, hypothesis tests, confidence intervals, linear regression) and be able to state the assumptions necessary for the validity of results.
- Set up and complete a least squares adjustment of measurement data.
- Analyse measurements and results using least squares and statistical tests.
Overview of Learning Activities
Learning will occur through a series of lectures, lab discussions, assignments, online and in-class tests.
You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course.
Overview of Learning Resources
RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course.
There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.
Overview of Assessment
Assessment Tasks
Assessment Task 1: Statistics Practical Assessments
Weighting 30%
This assessment task supports CLOs 1 & 2
Assessment Task 2: Statistics Group Assessment
Weighting 20%
This assessment task supports CLOs 1 & 2
Assessment Task 3: Least-squares Assignment
Weighting 20%
This assessment task supports CLOs 3 & 4
Assessment Task 4: Least-squares Practical Assessments
Weighting 30%
This assessment task supports CLOs 3 & 4
If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.