Fundamentals of Data Analysis - ZPEM2312
Faculty: UNSW Canberra at ADFA
School: School of Physical, Environmental and Mathematical Sciences @ UNSW Canberra at ADFA
Course Outline: ZPEM2312 Course Outline
Campus: UNSW Canberra at ADFA
Career: Undergraduate
Units of Credit: 6
EFTSL: 0.12500 (more info)
Indicative Contact Hours per Week: 4
Enrolment Requirements:
Exclusion: ZPEM1301, ZPEM1302, ZPEM1303, ZPEM1304, ZPEM2302, ZPEM2309, ZPEM2310 and ZBUS2104.
CSS Contribution Charge: 2 (more info)
Tuition Fee: See Tuition Fee Schedule
Further Information: See Class Timetable
Description
This course provides a foundation for quantitative methods applicable to students in their future careers. It teaches the fundamentals of data analysis with emphasis on the analysis of data arising from real-life situations across the disciplines. It focuses on the understanding of the concepts of statistics without overemphasizing the mathematical detail.
The course teaches the principles of good experimental design, as well as the interpretation and critical evaluation of statistical information presented in the media and in reports published by organisations. It introduces a computer software package, Excel, which is used for data exploration, presentation and analysis.
Main topics covered include: gathering, organising and summarising data; using graphical techniques to present statistical information; measures of location and spread; probability distributions such as the normal and binominal distributions; confidence intervals and hypothesis tests for a single sample; simple linear regression; contingency tables.
The course teaches the principles of good experimental design, as well as the interpretation and critical evaluation of statistical information presented in the media and in reports published by organisations. It introduces a computer software package, Excel, which is used for data exploration, presentation and analysis.
Main topics covered include: gathering, organising and summarising data; using graphical techniques to present statistical information; measures of location and spread; probability distributions such as the normal and binominal distributions; confidence intervals and hypothesis tests for a single sample; simple linear regression; contingency tables.