|Unit convenor and teaching staff
Unit convenor and teaching staff
Lead Unit Convenor/Lecturer
Contact via Email
please refer to iLearnSecond Unit Convenor/Lecturer
Contact via Email
please refer to iLearn
Admission to MRes
This unit introduces the foundation concepts of probability and statistics. The unit develops probability concepts, including random variables and distributions, independence, joint and conditional distributions, expectations, generating functions, distributions of sums of independent random variables and the Central Limit Theorem. The principles of statistical inference are discussed with a particular focus on point estimators, confidence intervals and hypothesis testing.
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
The online quiz, test and exam must be undertaken at the time indicated in the unit guide or on iLearn. Should these activities be missed due to illness or misadventure, students may apply for special consideration.
ASSIGNMENT SUBMISSION: Assignment submission will be online through the iLearn page.
Submit assignments online via the appropriate assignment link on the iLearn page. A personalised cover sheet is not required with online submissions. Read the submission statement carefully before accepting it as there are substantial penalties for making a false declaration.
You may submit as often as required prior to the due date/time. The assisgnment must be submitted by 5:00 pm on its due date. Please note that each submission will completely replace any previous submissions. It is in your interests to make frequent submissions of your partially completed work as insurance against technical or other problems near the submission deadline.
LATE SUBMISSION OF WORK: All assessment tasks must be submitted by the official due date and time. Should these assessments be missed due to illness or misadventure, students should apply for special consideration. In the case of a late submission for a non-timed assessment (e.g. an assignment), if special consideration has NOT been granted, a consistent penalty will be applied for the late submission as follows. A 12-hour grace period will be given after which the following deductions will be applied to the awarded assessment mark; 12 to 24 hours late = 10% deduction; for each day thereafter, an additional 10% per day or part thereof will be applied until five days beyond the due date. After this time (including weekends and/or public holidays), a mark of zero (0) will be given. Timed assessment tasks (e.g. iLean quiz, test, examination) do not fall under these rules.
FINAL EXAM POLICY: It is Macquarie University policy not to set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching semester, that is, the final day of the official examination period. The only excuse for not sitting an examination at the designated time is because of documented illness or unavoidable disruption. In these special circumstances, you may apply for special consideration via ask.mq.edu.au.
If you receive special consideration for the final exam, a supplementary exam will be scheduled in the interval between the regular exam period and the start of the next session. By making a special consideration application for the final exam you are declaring yourself available for a resit during this supplementary examination period and will not be eligible for a second special consideration approval based on pre-existing commitments. Please ensure you are familiar with the policy prior to submitting an application.
|University Examination Period
Mid-Semester Class Test
Invigilated Final Examination
1 If you need help with your assignment, please contact:
2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation
The unit is delivered by lectures (2 hours per week, starting in Week 1) and SGTAs (1 hour per week, starting in Week 2). All teaching material will be available on iLearn.
SGTA exercises will be available from iLearn prior to the SGTA. Students are expected to have attempted these prior to the SGTA. Solutions will be explained, with emphasis on any area students had trouble with. At the end of the week, these solutions will then be placed on iLearn. The web address is https://ilearn.mq.edu.au.
The R software (freely available online) will be used in the unit. Students need to practice how to use the software and be expected to use R for the assignment. Students should also note that the test and the final examination may contain inline R codes and output that students need to interpret to answer the questions.
There is no required textbook for this unit. Students may benefit from having access to the following background reference for additional reading and problems:
“Mathematical Statistics with Applications” W Mendenhall, D Wackerly and R Scheaffer (6th or 7th edition) - library call number is QA276.M426.
The following books may also be useful background references:
ROSS, S. A First Course in Probability (QA273.R83)
SCHEAFFER, R. L. Introduction to Probability and Its Applications (QA273.S357)
SMITH, P. J. Into Statistics (QA276.S615)
FREUND, J. E. Mathematical Statistics (QA276.F692)
HOEL, P. Introduction to Mathematical Statistics (QA276.H57)
HOGG, R.V. & TANIS, E.A. Probability and Statistical Inference (QA273.H694)
LARSON, H. Introduction to Probability Theory and Statistical Inference (QA273.L352)
SPIEGEL, M.R., SRINIVASAN, J. & SCHILLER, J.J. Schaum's outline of theory and problems of probability and statistics (QA273.25.S64)
WALPOLE, R.E. & MYERS, R.H. Probability and Statistics for Engineers and Scientists (TA340.W35)
HOGG, R.V. & CRAIG, A.T. Introduction to Mathematical Statistics (QA276.H59)
CASELLA, G. & BERGER, R.L. Statistical Inference (QA276.C37)
At least one copy of each of these is available in the Library, and extra copies may be available on the shelves for borrowing purposes.
It should be understood that there are variations in notation (and even in definition) from one reference book to another, and that the lecture material alone defines recommended notation. Note that all lecture notes will be available in pdf form on the Unit website on iLearn before the lecture. You are required to bring a hard or soft copy of the lecture notes to lectures.
Sample space, events. Axioms of probability, conditional probability. Bayes Theorem.
Random variables and probability distributions. Standard discrete and continuous distributions and their key characteristics. The Poisson process.
Expected values (discrete and continuous) and their properties. Measures of variation. Quantiles. Moments (raw and central). Interpretation of moments (skewness, kurtosis etc.).
Sums of independent random variables. Discrete and continuous convolutions with applications. Transformations (monotonic and non-monotonic) of continuous random variables. Transformation of a continuous random variable to one with a uniform distribution, with applications to simulation.
Probability generating functions and moment generating functions with properties and applications. The moment generating function of a sum of independent random variables. The Central Limit Theorem and applications.
Multivariate (particularly bivariate) random variable theory (continuous and discrete). Marginal and conditional distributions and expectations. Covariance and correlation.
Exploratory data analysis including measures of association and principal component analysis.
Random sampling and sampling distributions.
Point estimators and their properties. MLEs and asymptotic results and bootstrapping.
Interval estimators, their properties.
Hypothesis testing, including likelihood ratios and goodness of fit.
Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact firstname.lastname@example.org
At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
The Writing Centre provides resources to develop your English language proficiency, academic writing, and communication skills.
The Library provides online and face to face support to help you find and use relevant information resources.
Macquarie University offers a range of Student Support Services including:
For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/.
When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
Unit information based on version 2022.02 of the Handbook