• Class Number 2497
• Term Code 2930
• Class Info
• Unit Value 6 units
• Mode of Delivery In Person
• COURSE CONVENER
• Dr Laurence Field
• LECTURER
• Dr Laurence Field
• Class Dates
• Class Start Date 25/02/2019
• Class End Date 31/05/2019
• Census Date 31/03/2019
• Last Date to Enrol 04/03/2019
SELT Survey Results

Statistical Techniques (STAT1003)

This course introduces students to the philosophy and methods of modern statistical data analysis and inference, with a particular focus on applications to the life sciences.

Why and how to use: tables to organise and summarise data; graphics to present statistical information; measures of location and spread for univariate distributions. Concepts of randomness, uncertainty, random variables, probability distributions (including uniform, binomial, normal), and sampling distributions and how to apply these for inference from small and large samples through: confidence intervals; hypothesis testing in one and two sample cases; p-values; linear regression models and analysis of variance. Examples and applications will be drawn extensively from the life sciences, particularly Biology. The course has a strong emphasis on computing and graphical methods, and uses a variety of real-world problems to motivate the theory and methods required for carrying out statistical data analysis. This course makes extensive use of R statistical analysis package interfaced through R Studio.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

1. Summarise and graph data appropriately;
2. Work with random variables and probability distributions and understand the rationale behind them;
3. Understand and use the normal distribution appropriately;
4. Identify when and how to carry out basic statistical inference including confidence intervals, hypothesis testing and regression and ANOVA; and,
5. Identify contexts in which a method may be appropriate (e.g. using a large sample method when sample size is small).

Research-Led Teaching

This course aims to provide you with a foundation in statistical thinking and evidence-based logic, two elements that are integral to any academic program and life in the work force beyond your university degree. Almost all areas of research require both elements. Any research that involves data also involves statistical computing. We do so with the software package R (https://www.r-project.org) at an elementary level.

I will also introduce examples, whenever applicable, from my current research areas in class to further illustrate concepts and the use of statistics.

Required Resources

Course text (free e-book): OpenIntro Statistics, 3rd Edition by David M Diez, Christopher D Barr, Mine Çetinkaya-Rundel (https://www.openintro.org/stat/)

Hand-held non-programmable calculator

Staff Feedback

Students will be given feedback in the following forms in this course:

• Written feedback for one mid-semester examination and one assignment;
• Verbal feedback during tutorial/lab sessions;
• In-person consultation with the lecturer or tutor during office hours.

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Other Information

Assessment Requirements

As a further academic integrity control, students may be selected for a 15 minute individual oral examination of their written assessment submissions.

Any student identified, either during the current semester or in retrospect, as having used ghost-writing services will be investigated under the University’s Academic Misconduct Rule.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction to Data
2 Introduction to Data
3 Introduction to Probability Theory Quiz week 5, mid-semester exam week 6 or 7
4 Introduction to Probability Theory
5 Introduction to Probability Theory
6 Introduction to Probability Theory
7 Statistical Inference and Simple Linear Regression Assignment due week 11
8 Statistical Inference and Simple Linear Regression
9 Statistical Inference and Simple Linear Regression
10 Statistical Inference and Simple Linear Regression
11 Statistical Inference and Simple Linear Regression
12 Statistical Inference and Simple Linear Regression

Tutorial Registration

Tutorial signup for this course will be done via the Wattle website. Detailed information about signup times will be provided on Wattle. When tutorials are available for enrolment, follow these steps:

1. Log on to Wattle, and go to the course site.

2. Click on the link “Tutorial enrolment”.

3. On the right of the screen, click on the tab “Become Member of...” for the tutorial class you wish to enter.

If you need to change your enrolment, you will be able to do so by clicking on the tab “Leave group...” and then re-enrol in another group. You will not be able to enrol in groups that have reached their maximum number. Please note that enrolment in ISIS must be finalised for you to have access to Wattle.”

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Quiz 5 % 25/03/2019 26/03/2019 1-2
Mid-Semester Examination 20 % 01/04/2019 16/04/2019 1-2
Assignment 10 % 20/05/2019 28/05/2019 1-5
Final Examination 65 % 06/06/2019 04/07/2019 1-5

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Value: 5 %
Due Date: 25/03/2019
Return of Assessment: 26/03/2019
Learning Outcomes: 1-2

Quiz

An online quiz will be held via the Wattle site during week 5, covering material from Weeks 1–4, inclusive. The quiz will be available only on Monday 25 March until 23:59. Students have 30 minutes to complete the quiz from when they first open the quiz. Quiz answers will be available to students immediately after they finish the online quiz.

Value: 20 %
Due Date: 01/04/2019
Return of Assessment: 16/04/2019
Learning Outcomes: 1-2

Mid-Semester Examination

The mid-semester examination will be held during week 6 or 7 (subject to confirmation from the Examinations Office), covering material from Weeks 1–6, inclusive. It will be a 1½-hour closed-book examination.

Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Further information about the examination will be provided in class and on Wattle closer to the time of the examination.

Value: 10 %
Due Date: 20/05/2019
Return of Assessment: 28/05/2019
Learning Outcomes: 1-5

Assignment

Value: 65 %
Due Date: 06/06/2019
Return of Assessment: 04/07/2019
Learning Outcomes: 1-5

Final Examination

The final examination will be 3-hour closed-book examination. Each student will be allowed to bring in a single handwritten double-sided A4 sheet of notes.

Centrally administered examinations through Examinations, Graduations & Prizes will be timetabled prior to the examination period. Please check ANU Timetabling for further information. Further information about the examination will be provided in class and on Wattle closer to the time of the examination.

Online Submission

You will be required to sign a physical Assignment Cover Sheet as part of the submission of your assignment. Assignments must be submitted in hard copy to the RSFAS office, in person. No online submission is permitted or accepted.

Hardcopy Submission

Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Convener

 Dr Laurence Field +61 2 612 56710 laurence.field@anu.edu.au

Research Interests

Probability and Stochastic Processes

Dr Laurence Field

 Wednesday 12:00 14:00 Wednesday 12:00 14:00

Instructor

 Dr Laurence Field +61 2 612 56710 laurence.field@anu.edu.au

Dr Laurence Field

 Wednesday 12:00 14:00 Wednesday 12:00 14:00