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Applied Data Analysis for Civil and Natural Resources Engineers provides an analytical foundation for subsequent third- and fourth-year courses, providing fundamental skills in field survey techniques, geospatial analysis, exploratory data analysis, hypothesis testing and regression. These generic skills are developed using real-world examples and datasets, and are applicable in subsequent courses in in the undergraduate degree programme. The course is based on field survey activities in the first two weeks, and a series of weekly computer laboratories over the semester, supported by recorded lectures, tutorials and readings.
1. Whakamahuki - OverviewENCN205 Applied Data Analysis for Civil and Natural Systems provides key concepts and skills to support the reminder of the degree programme. The course is delivered in two parts: 1) Field Surveying and Applications in Geographic Information Systems; and 2) Statistics and Optimisation.Part 1: Field Surveying and Applications of Geographic Information SystemsField Surveying and Applications of Geographic Information Systems (GIS) provides foundational skills in basic field data collection and data processing, accessing spatial data online, conducting spatial analysis, and presenting outputs in map and graphical form, to answer questions relevant to civil and natural systems. It assumes no previous knowledge of GIS, but assumes basic competency in file management using Microsoft Windows Explorer, and in using Microsoft Excel and Word. This part is designed to make you a competent and confident user of spatial data to support your engineering activities. This is done through series of field activities, computer laboratories with assessed outputs, and a final assignment that brings together the various GIS tools you have mastered. After this part, you will be able to make maps and conduct spatial analysis for any other relevant course activities in third and fourth year.Part 2: Statistics and OptimisationStatistics and Optimisation builds directly on the numerical methods in EMTH171 and on probability and statistical material taught in EMTH210 and EMTH118/119. The section starts with exploratory data analysis and data visualisation which provide you tool to browse your data file preliminarily, and followed by random sampling and Monte Carlo methods for numerical simulations, as well as hypothesis testing extended from EMTH210. Linear regression, Bootstrapping and data diagnosis are included to discover knowledge from data and to make statistical inferences. This is followed by basic principles of optimisation methods and their applications in engineering and data analysis. You will learn skills such as linear programming to solve a range of optimisation problems in engineering. The concepts and techniques developed will appear in a number of fourth year courses, in particular all those that require the data manipulation or statistical characterisation of experimental or observational data, and the use of optimisation methods. In all sections the emphasis is on the application of statistics and optimisation methods to civil and natural resources engineering.
Part 1: Field Surveying and Applications of Geographic Information Systems1. To introduce students to fundamental field survey techniques (e.g. total station, GNSS survey) and post-processing used in industry to develop topographic maps for construction projects. (Washington Accord Attribute WA1, WA5) (UC EIE)2. To familiarise students with spatial coordinate systems and GIS data formats (vector and raster). (Washington Accord Attribute WA1, WA5) (UC EIE)3. To know how to use spatial and attribute queries to answer questions relevant to civil and natural systems applications. (Washington Accord Attribute WA1, WA5) (UC EIE)4. To be able to create vector and raster datasets and conduct spatial analysis with them. (Washington Accord Attribute WA1, WA5) (UC EIE)5. To be able to make maps using cartographic principles, and to export GIS spatial analysis and cartographic outputs to spreadsheets and other documents. (Washington Accord Attribute WA1, WA5)Part 2: Statistics and Optimisation1. To understand hypothesis testing and apply hypothesis test to different situations. (Washington Accord Attribute WA1, WA5) (UC EIE)2. Introduce analytical approaches to examine dependence between different quantities for which observational data is available and use them for statistical inferences. (Washington Accord Attribute WA1, WA5) (UC EIE)3. To be able to design and carry out statistical numerical simulations. (Washington Accord Attribute WA1, WA5) (UC EIE)4. To understand basic concept of optimisation methods and their applications in engineering. (Washington Accord Attribute WA1, WA5) (UC EIE)5. To be able to solve numerically a range of optimisation problems in engineering. (Washington Accord Attribute WA1, WA5) (UC EIE)
COSC131
EMTH210
Students must attend one activity from each section.
Derek Li
Tom Logan
Dave Bracken
The assessment for this course has five components:1) Survey activity attendance and outputs assessments.2) GIS computer laboratory outputs assessments.3) GIS assignment.4) Statistics and optimisation self-studying quiz and tutorial submission on Learn.5) Final exam (covering statistics and optimisation).Special ConsiderationsStudents may apply for special consideration if their performance in an assessment is affected by extenuating circumstances beyond their control. The applicability and academic remedy/action associated with the special consideration process is listed for each assessment item below. Applications for special consideration should be submitted via the Examinations Office website http://www. canter bury.ac.nz/exams/ within 5 days of the assessment.Surveying Outputs: Special consideration is not applicable as the individual activity are worth <10%. Students will have until the end of week 3 to complete all lab output submissions. Beyond this, students will need to demonstrate significant impairment supported by medical evidence to have late submissions considered. Late submissions may be considered on a case-by-case basis.GIS Lab Outputs: Special consideration is not applicable as the individual labs are worth <10%. Students will have until the end of week 5 to complete all lab output submissions. Beyond this, students will need to demonstrate significant impairment supported by medical evidence to have late submissions considered. Late submissions may be considered on a case-by-case basis.GIS Assignment: The assignment instructions will be posted by end of week 2, and students will be expected to commence work on the assignment then. Students will need to demonstrate significant impairment supported by medical evidence to have late submissions considered. Late submissions may be considered on a case-by-case basis.Statistics and Optimisation Lab Quizzes/ self-assessment: Special consideration is not applicable as the individual LEARN quizzes are worth <10% of the course grade. No alternative arrangements will be offered for any quizzes that are missed regardless of the circumstances. Reasonable extensions may be granted by communicating with corresponding lecturers.Final exam: Students will be offered an equivalent alternative exam that will replace their original exam mark.Note on equivalent alternative assessments: The academic remedy for a special consideration assessed at a moderate level or higher is an equivalent exam. The alternative exam will be held on campus during the week of November 24th. The mark on the alternative exam will replace the original exam mark in the course grade calculation unless a student declines or does not respond to the offer of the alternative exam, in which case the original mark will be used. Students will not be advised of their original mark as part of this process. All communication associated with special considerations will be conducted using official UC email accounts. The offer to sit an alternative assessment will come with a date and time. Students will have a clearly specified amount of time to respond to the offer. Failure to respond in the specified time frame will be interpreted as a declined offer. If a student has applied for special consideration but the application has not yet been approved, they may be permitted to sit the alternative exam, but the mark will not be applied until the special consideration application has been approved.
All course materials will be made available through Learn and the CSSE quiz server. This course does not have a required text and instead provides notes and other resources on LEARN. Furthermore, a number of articles will be posted on the class LEARN site as recommended reading. Please note that all lecture recordings, made available through LEARN, are copyright and are not for public dissemination.
Ki te mea he taumahatanga āu - Special Considerations Students may apply for special consideration if their performance in an assessment is affected by extenuating circumstances beyond their control. The applicability and academic remedy/action associated with the special consideration process is listed for each assessment item below. Applications for special consideration should be submitted via the Examinations Office website http://www. canter bury.ac.nz/exams/ within 5 days of the assessment.GIS Lab OutputsSpecial consideration is not applicable as the individual labs are worth <10%. Students will have until the end of week 5 to complete all lab output submissions. Beyond this, students will need to demonstrate significant impairment supported by medical evidence to have late submissions considered. Late submissions may be considered on a case-by-case basis.GIS AssignmentThe assignment instructions will be posted by end of week 2, and students will be expected to commence work on the assignment then. Students will need to demonstrate significant impairment supported by medical evidence to have late submissions considered. Late submissions may be considered on a case-by-case basis.Statistics and Optimisation Lab Quizzes/ self-assessmentSpecial consideration is not applicable as the individual LEARN quizzes are worth <10% of the course grade. No alternative arrangements will be offered for any quizzes that are missed regardless of the circumstances. Reasonable extensions may be granted by communicating with corresponding lecturers.Final exam - Serious/Severe impact Students will be offered an equivalent alternative exam that will replace their original exam mark. The date of this alternative exam will be released after the exam period.Moderate Impairment - A derived mark will be applied based on the overall performance in the quiz, tutorials and the understanding of knowledge presented in the exam script.Note: All communication associated with the arrangement of equivalent alternative tests/exams will be conducted using official UC email accounts. The offer to sit an alternative assessment will come with a specific time and date. Students will have a clearly specified amount of time to respond to the offer to sit the alternative assessment. If the offer is declined, the original assessment mark will be used to compute the course grade. Failure to respond in the specified time frame will be interpreted as a declined offer.Generative AI use in this course It is not practical to regulate the use of Generative AI (e.g., ChatGPT) for internal assessments on this course – weekly homework and quiz assignments. Students are allowed to use these tools in whichever manner they see fit. However, you should be aware of the risks, which are described below.Research clearly shows that the unrestricted use of ChatGPT by students during mathematical education leads to decreased performance on external assessment (which happens to comprise most of your grade in this course). For instance, this study showed a 17% reduction in test performance, more than three grade points.The primary mechanisms leading to adverse outcomes appear to be (1) shallow learning, where AI prevents you spending sufficient time with the material to obtain a deep understanding of it, and (2) AI dependency, where overuse of the tool leads to an inability to apply methods or think critically once it is taken away.If you intend to use Generative AI on this course, consider prompting with some basic guardrails to prevent the above impacts on your learning:“You are a math tutor helping me with a homework problem. Please suggest one (and only one) next step for me to consider on the following problem. Don’t complete the problem for me. **paste your problem**.”“You are a coding tutor helping me with a homework problem. Here is some code I have written and the error that I am getting. Please give me some hints about how I can fix this. Do not give me the corrected code though. **paste your code and error message**.”Even with the guardrails, a helpful Generative AI will frequently just give you the solution to a problem, cheating you of the opportunity to learn it yourself.
Domestic fee $1,122.00
International fee $6,238.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Civil and Natural Resources Engineering .