Unit convenor and teaching staff |
Unit convenor and teaching staff
Lead Unit Convenor/Lecturer
Georgy Sofronov
Contact via Email
12WW 529
please refer to iLearn
Second Unit Convenor/Lecturer
Connor Smith
Contact via Email
12WW 617
please refer to iLearn
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Credit points |
Credit points
10
|
Prerequisites |
Prerequisites
STAT272 or STAT2372
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Corequisites |
Corequisites
|
Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit introduces the foundation concepts of statistics. The unit begins with a discussion of the aims of data analysis and the objectives of principal component analysis. A discussion of random samples and their use in drawing inferences about a population is then provided. The principles of statistical inference are developed 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:
To pass this unit you must achieve a total mark equal to or greater than 50%.
There are no hurdle assessments for this unit.
The 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 11:55pm 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 ASSESSMENT SUBMISSION PENALTY: Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of '0' will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11:55 pm. A 1-hour grace period is provided to students who experience a technical concern.
For any late submission of time-sensitive tasks, such as scheduled tests and exams, students need to submit an application for Special Consideration.
In this unit, late submissions will be accepted as follows:
SPECIAL CONSIDERATION: The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment. If you experience circumstances or events that affect your ability to complete the assessments in this unit on time, please inform the convenor and submit a Special Consideration request through ask.mq.edu.au.
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.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Assignment 1 | 10% | No | Week 5 |
Test | 20% | No | Week 8 |
Assignment 2 | 10% | No | Week 11 |
Final Examination | 60% | No | Exam Period |
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 8 hours
Due: Week 5
Weighting: 10%
Assignment
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 1 hours
Due: Week 8
Weighting: 20%
Mid-Semester Test
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 8 hours
Due: Week 11
Weighting: 10%
Assignment
Assessment Type 1: Examination
Indicative Time on Task 2: 3 hours
Due: Exam Period
Weighting: 60%
Formal invigilated examination testing the learning outcomes of the unit.
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 supported statistical software for this unit is R/RStudio. Students need to practice how to use the software and be expected to conduct their analyses using R/RStudio for the assignments. Students should also note that the test and the final examination may involve data analysis that contains inline R codes and output that students need to interpret to answer the questions.
Recommended: Mendenhall W, Wackerly D and Scheaffer R. “Mathematical Statistics with Applications”, Seventh Edition QA276 .M426 2008. The Library also holds copies of the sixth and previous editions as well as the Student solutions manual. The following books are useful references for this unit:
Authors | Title | Library Call No. |
---|---|---|
Bain, L.J. & Engelhardt, M. | Introduction to Probability and Mathematical Statistics | QA273.B2546/1992 |
Casella, G. & Berger, R.L. | Statistical Inference | QA276.C37/2002 |
Conover, W.J. | Practical Nonparametric Statistics | QA278.8.C65/1999 |
Hogg, R.V. & Craig, A.T. | Introduction to Mathematical Statistics | QA276.H59/1995 |
Larson, H.J. | Introduction to Probability Theory and Statistical Inference | QA273.L352/1982 |
Walpole, R.E. & Myers, R.H. | Probability and Statistics for Engineers and Scientists | TA340.W35/1993 |
We will communicate with you via your university email or through announcements on iLearn. Queries to the convenors can either be placed on the iLearn discussion board or sent to the staff email address from your university email address.
TOPIC |
MATERIAL COVERED |
---|---|
1 |
Introduction. Statistical terms and notations. |
2 |
Random sampling and sampling distributions. |
3 |
Estimation and estimators. Point estimation methods, including the method of moments and maximum likelihood. Properties of estimators. Asymptotic (large sample) properties. |
4 |
Confidence intervals. |
5 |
Hypothesis testing and goodness of fit. |
6 |
One-way analysis of variance (ANOVA) and multiple comparisons. |
7 |
Transformations, non-parametric tests, power and data management. |
8 |
Two-way ANOVA and multiple regression. |
9 |
Exploratory data analysis. |
10 | Data analysis. |
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Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
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We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page. Student feedback from the previous offering of this unit was very positive overall, with students pleased with the clarity around assessment requirements and the level of support from teaching staff. As such, no change to the delivery of the unit is planned, however we will continue to strive to improve the level of support and the level of student engagement.
Unit information based on version 2024.01R of the Handbook