Fundamentals of Statistics
|Course code STAT2010||Units 10||Level 2000||Faculty of Science and Information TechnologySchool of Mathematical and Physical Sciences|
Statistics is about using data to describe, summarise and model the world around us. Whether it's cricket scores, the stock market or global warming, we need to understand probability and data analysis in order to make informed decisions and predictions.
This course develops basic concepts of probability, random variables and their distributions, and then shows how these ideas provide the theoretical foundation for data analysis through statistical modelling, estimation and hypothesis testing.
Although a variety of real problems are used to illustrate the concepts and methods, the emphasis in this course is on statistical theory. STAT2010 is an essential part of a Statistics major providing the necessary background for most 3000 level statistics courses. STAT2010 is also suitable for those students in a range of undergraduate programs who wish to understand why statistical methods work (and not just how to operate a statistical software package without any true comprehension).
Available in 2014
|Objectives||On successful completion of this course, students will be able to:|
1. explain the mathematical basis of probability
2. define real world problems in statistical terms
3. recognize common probability distributions and their applications
4. solve a range of problems involving expectation and transformation of random variables
5. use simple Monte Carlo simulation methods
6. use fundamental principles of estimation to derive statistical estimators
7. explain the principles of hypothesis testing and derive and use simple hypothesis tests
8. develop simple statistical models useful in analysing real problems.
|Content||The course will include the following topics|
. Random variables and their distributions
. Expected values
. Functions of random variables
. Joint distributions
. Samples, statistics, sampling distributions and limit theorems
. Hypothesis testing
. Simple statistical models - regression and ANOVA
|Assumed Knowledge||Introductory course in applied statistics (eg STAT1070) and calculus of two variables (eg MATH1120).|
|Modes of Delivery||Internal Mode|
|Contact Hours||Lecture: for 2 hour(s) per Week for Full Term|
Computer Lab: for 2 hour(s) per Week for Full Term
|Timetables||2014 Course Timetables for STAT2010|