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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 SystemsTo 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.To familiarise students with spatial coordinate systems and GIS data formats (vector and raster).To know how to use spatial and attribute queries to answer questions relevant to civil and natural systems applications.To be able to create vector and raster datasets and conduct spatial analysis with them.To be able to make maps using cartographic principles, and to export GIS spatial analysis and cartographic outputs to spreadsheets and other documents.Part 2: Statistics and OptimisationTo understand hypothesis testing and apply hypothesis test to different situations.To introduce analytical approaches to examine dependence between different quantities for which observational data is available and use them for statistical inferences.To be able to design and carry out statistical numerical simulations.To understand basic concept of optimisation methods and their applications in engineering.To be able to solve numerically a range of optimisation problems in engineering.
Students must attend one activity from each section.
The assessment for this course has four components:1. GIS computer laboratory outputs assessments.2. GIS assignment.3. Statistics and optimisation self-studying quiz and tutorial submission on Learn.4. Final exam (covering statistics and optimisation). All of the material covered in the programming section (section 1) will be assessed in the mid-semester test. The second and third sections will be tested in the final exam.
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.
Domestic fee $1,059.00
International fee $6,000.00
* 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