Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
Basic statistical concepts and techniques such as descriptive statistics, probability concepts, theoretical distributions, inferential statistics (confidence intervals and hypothesis testing) are applied in business and economics.
ECON1310 is an introductory course in quantitative analysis for business and economics. The course covers a variety of techniques applicable to the presentation, interpretation and use of data. The main emphasis is inferential statistics with estimation and hypothesis testing techniques being an important part of the course. Inferential statistics is continued in the simple linear regression topic. There is an emphasis on the use of Excel for analysis and presentation.
This course is widely regarded as challenging by many students. One reason is that the work is very cumulative. This means that it is exceptionally difficult to catch up if a student gets behind in the work. Success in the subject depends on keeping up-to-date. With this in mind, each topic is progressively assessed using various computer managed quizzes throughout the course.
As well as covering concepts that are an essential part of the analytical tool box for well-trained professionals, ECON1310 provides a foundation that is critical for success in later statistical courses, particularly ECON2300 Introductory Econometrics.
Course requirements
Assumed background
Algebra from either Queensland High School Maths B, Mathematical Methods, or equivalent.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
Maths B; or Maths C; or MATH1040; or one of Mathematical Methods or Specialist Mathematics (Units 3 and 4, C)
Incompatible
You can't enrol in this course if you've already completed the following:
CHEE2010 or 3010 or CIVL2530 or MINE3214 or PHRM1020 or STAT1201 or 1301 or 2201 or 2203
Course contact
School enquiries
All enquiries regarding student and academic administration (i.e. non-course content information, e.g., class allocation, timetables, extension to assessment due date, etc.) should be directed to enquiries@economics.uq.edu.au.
Enquiries relating specifically to course content should be directed to ECON1310@uq.edu.au.
Course staff
Lecturer
Tutor
Senior tutor
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Live lectures only will be delivered at St Lucia. Students need to sign-on to attend the live weekly lectures. All students must sign on to a live tutorial group at St Lucia via My Timetable (available through my.UQ dashboard). This is essential in order to attend and pass the required Identity Verified Assessment (IVA) tutorial activities that run in selected tutorials during the semester. Students must enrol in a tutorial group prior to Week 2 and attend the same tutorial group each week. Students must only attend the tutorial they sign-on to for the compulsory IVA tutorial activities, otherwise they will be required to leave. Students are not allowed to swap tutorials after census date.
• Lecture Sign On: Please refer to My Timetable (available via the my.UQ dashboard).
• Tutorial Preferencing: Please refer to My Timetable (available via the my.UQ dashboard) for more information on the tutorial preferencing and allocation process.
• Consultation Sign On: There is NO need to sign on to attend consultation. The weekly consultation timetable will be posted in teaching Week 1 under the "Course Help" tab of the ECON1310 Blackboard site.
Tutorials and Consultations commence in Teaching Week 2.
Please see the Learning Activities section of this Course Profile for the timetabling implications of public holidays.
Public Holidays: Wed 14 August (Royal Queensland Show), Mon 7 October (King's Birthday).
In-Semester Break:ᅠ 23 September - 27 September. Semester 2 classes recommence Mon 30 September.
Students should refer to the timetable prior to the commencement of classes to ensure that they have the most up to date information, as from time to time late room changes may occur.
Aims and outcomes
The aim of the course is for students to develop an ability to apply inferential statistics techniques to independently solve practical problems and to then explain the solutions using everyday language.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Use fundamental statistics terminology.
LO2.
Apply theoretical concepts to construct analytical statistical techniques.
LO3.
Describe the statistical techniques needed to solve particular problem types.
LO4.
Conduct statistical analysis of data so as to draw statistical conclusions.
LO5.
Communicate statistical findings for practical and professional use.
Assessment
Assessment summary
Category | Assessment task | Weight | Due date |
---|---|---|---|
Quiz |
CML 1 - Descriptive Statistics
|
5% (Best 5 out of 6) |
CML 1 (1st attempt) 31/07/2024 - 13/08/2024 CML 1 (2nd attempt) 15/08/2024 - 16/08/2024
The CML first attempt opens at 9am and closes at 4pm. The CML optional second attempt opens at 9am and closes at 4pm. |
Quiz |
CML 2 - Probability
|
5% (Best 5 out of 6) |
CML 2 (1st attempt) 15/08/2024 - 27/08/2024 CML 2 (2nd attempt) 28/08/2024 - 30/08/2024
The CML first attempt opens at 9am and closes at 4pm. The CML optional second attempt opens at 9am and closes at 4pm. |
Quiz |
CML 3 - Normal and Sampling Distributions
|
5% (Best 5 out of 6) |
CML 3 (1st attempt) 28/08/2024 - 10/09/2024 CML 3 (2nd attempt) 11/09/2024 - 13/09/2024
The CML first attempt opens at 9am and closes at 4pm. The CML optional second attempt opens at 9am and closes at 4pm. |
Quiz |
LBRT #1 Problem Set & IVA Tutorial Activity
|
25% |
LBRT #1 (1st attempt) 5/09/2024 - 6/09/2024 LBRT #1 (2nd attempt) 12/09/2024 - 13/09/2024 IVA (Tutorial 8) 16/09/2024 - 20/09/2024
The LBRT first attempt opens at 9am and closes at 4pm. The LBRT optional second attempt opens at 9am and closes at 4pm. IVA tutorial activity at start of Tutorial 8 (i.e. in teaching week 9). |
Quiz |
CML 4 - Confidence Intervals
|
5% (Best 5 of 6) |
CML 4 (1st attempt) 11/09/2024 - 1/10/2024 CML 4 (2nd attempt) 2/10/2024 - 4/10/2024
The CML first attempt opens at 9am and closes at 4pm. The CML optional second attempt opens at 9am and closes at 4pm. |
Quiz |
CML 5 - Hypothesis Testing
|
5% (Best 5 of 6) |
CML 5 (1st attempt) 2/10/2024 - 15/10/2024 CML 5 (2nd attempt) 16/10/2024 - 18/10/2024
The CML first attempt opens at 9am and closes at 4pm. The CML optional second attempt opens at 9am and closes at 4pm. |
Quiz |
LBRT #2 Problem Set & IVA Tutorial Activity
|
25% |
LBRT #2 (1st attempt) 10/10/2024 - 11/10/2024 LBRT #2 (2nd attempt) 17/10/2024 - 18/10/2024 IVA (Tutorial 12) 21/10/2024 - 25/10/2024
The LBRT first attempt opens at 9am and closes at 4pm. The LBRT optional second attempt opens at 9am and closes at 4pm. IVA tutorial activity at start of Tutorial 12 (i.e. in teaching week 13) |
Quiz |
CML 6 - Simpler Linear Regression
|
5% (Best 5 of 6) |
16/10/2024 - 25/10/2024
NO SECOND ATTEMPT The CML opens at 9am and closes at 4pm. |
Quiz |
LBRT #3 Problem Set (No IVA Tutorial Activity)
|
25% |
LBRT #3 (1st attempt) 7/11/2024 - 8/11/2024 LBRT #3 (1st attempt) 12/11/2024 - 13/11/2024
The LBRT first attempt opens at 9am and closes at 4pm. The LBRT optional second attempt opens at 9am and closes at 4pm. |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
CML 1 - Descriptive Statistics
- Hurdle
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 5% (Best 5 out of 6)
- Due date
CML 1 (1st attempt) 31/07/2024 - 13/08/2024
CML 1 (2nd attempt) 15/08/2024 - 16/08/2024
The CML first attempt opens at 9am and closes at 4pm.
The CML optional second attempt opens at 9am and closes at 4pm.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A set of questions on lectures and tutorials 1 & 2.
Note that a student's best 5 out of 6 CML quizzes will be used in calculating the aggregate result that contributes to a student's overall mark (see full details under Additional Assessment Information). If there are changes relating to any CML quiz dates and times (considered to be unlikely), they will be advised in advance to students via Blackboard. Students should monitor Blackboard regularly for CML quiz information.
CML quizzes evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Enter answers into Blackboard by due date and time.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
CML 2 - Probability
- Hurdle
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 5% (Best 5 out of 6)
- Due date
CML 2 (1st attempt) 15/08/2024 - 27/08/2024
CML 2 (2nd attempt) 28/08/2024 - 30/08/2024
The CML first attempt opens at 9am and closes at 4pm.
The CML optional second attempt opens at 9am and closes at 4pm.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A set of questions on lectures and tutorials 3 & 4.
Note that a student's best 5 out of 6 CML quizzes will be used in calculating the aggregate result that contributes to a student's overall mark (see full details under Additional Assessment Information). If there are changes relating to any CML quiz dates and times (considered to be unlikely), they will be advised in advance to students via Blackboard. Students should monitor Blackboard regularly for CML quiz information.
CML quizzes evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Enter answers into Blackboard by due date and time.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
CML 3 - Normal and Sampling Distributions
- Hurdle
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 5% (Best 5 out of 6)
- Due date
CML 3 (1st attempt) 28/08/2024 - 10/09/2024
CML 3 (2nd attempt) 11/09/2024 - 13/09/2024
The CML first attempt opens at 9am and closes at 4pm.
The CML optional second attempt opens at 9am and closes at 4pm.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A set of questions on lectures and tutorials 5 & 6.
Note that a student's best 5 out of 6 CML quizzes will be used in calculating the aggregate result that contributes to a student's overall mark (see full details under Additional Assessment Information). If there are changes relating to any CML quiz dates and times (considered to be unlikely), they will be advised in advance to students via Blackboard. Students should monitor Blackboard regularly for CML quiz information.
CML quizzes evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Enter answers into Blackboard by due date and time.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
LBRT #1 Problem Set & IVA Tutorial Activity
- Hurdle
- Identity Verified
- Mode
- Written
- Category
- Quiz
- Weight
- 25%
- Due date
LBRT #1 (1st attempt) 5/09/2024 - 6/09/2024
LBRT #1 (2nd attempt) 12/09/2024 - 13/09/2024
IVA (Tutorial 8) 16/09/2024 - 20/09/2024
The LBRT first attempt opens at 9am and closes at 4pm.
The LBRT optional second attempt opens at 9am and closes at 4pm.
IVA tutorial activity at start of Tutorial 8 (i.e. in teaching week 9).
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
LBRT #1 will involve solving problems based on the learning materials covered in Weeks 1 to 4 inclusively. This includes all learning materials presented in Lectures 1 to 4, the associated tutorials, as well as CML1 and CML2. All answers must be entered into Blackboard by the due date and time.
LBRTs evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
CML 4 - Confidence Intervals
- Hurdle
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 5% (Best 5 of 6)
- Due date
CML 4 (1st attempt) 11/09/2024 - 1/10/2024
CML 4 (2nd attempt) 2/10/2024 - 4/10/2024
The CML first attempt opens at 9am and closes at 4pm.
The CML optional second attempt opens at 9am and closes at 4pm.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A set of questions on lectures and tutorials 7 & 8.
Note that a student's best 5 out of 6 CML quizzes will be used in calculating the aggregate result that contributes to a student's overall mark (see full details under Additional Assessment Information). If there are changes relating to any CML quiz dates and times (considered to be unlikely), they will be advised in advance to students via Blackboard. Students should monitor Blackboard regularly for CML quiz information.
CML quizzes evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Enter answers into Blackboard by due date and time.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
CML 5 - Hypothesis Testing
- Hurdle
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 5% (Best 5 of 6)
- Due date
CML 5 (1st attempt) 2/10/2024 - 15/10/2024
CML 5 (2nd attempt) 16/10/2024 - 18/10/2024
The CML first attempt opens at 9am and closes at 4pm.
The CML optional second attempt opens at 9am and closes at 4pm.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A set of questions on lectures and tutorials 9 & 10.
Note that a student's best 5 out of 6 CML quizzes will be used in calculating the aggregate result that contributes to a student's overall mark (see full details under Additional Assessment Information). If there are changes relating to any CML quiz dates and times (considered to be unlikely), they will be advised in advance to students via Blackboard. Students should monitor Blackboard regularly for CML quiz information.
CML quizzes evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Enter answers into Blackboard by the due date and time.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
LBRT #2 Problem Set & IVA Tutorial Activity
- Hurdle
- Identity Verified
- Mode
- Written
- Category
- Quiz
- Weight
- 25%
- Due date
LBRT #2 (1st attempt) 10/10/2024 - 11/10/2024
LBRT #2 (2nd attempt) 17/10/2024 - 18/10/2024
IVA (Tutorial 12) 21/10/2024 - 25/10/2024
The LBRT first attempt opens at 9am and closes at 4pm.
The LBRT optional second attempt opens at 9am and closes at 4pm.
IVA tutorial activity at start of Tutorial 12 (i.e. in teaching week 13)
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
LBRT #2 will involve solving problems based on the learning materials covered in Weeks 5 to 8 inclusively. This includes all learning materials presented in Lectures 5 to 8, the associated tutorials, as well as CML3 and CML4. All answers must be entered into Blackboard by the due date and time.
LBRTs evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
CML 6 - Simpler Linear Regression
- Hurdle
- Online
- Mode
- Written
- Category
- Quiz
- Weight
- 5% (Best 5 of 6)
- Due date
16/10/2024 - 25/10/2024
NO SECOND ATTEMPT
The CML opens at 9am and closes at 4pm.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
A set of questions on lectures and tutorials 11 & 12.
Note that a student's best 5 out of 6 CML quizzes will be used in calculating the aggregate result that contributes to a student's overall mark (see full details under Additional Assessment Information). If there are changes relating to any CML quiz dates and times (considered to be unlikely), they will be advised in advance to students via Blackboard. Students should monitor Blackboard regularly for CML quiz information.
CML quizzes evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Enter answers into Blackboard by the due date and time.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
LBRT #3 Problem Set (No IVA Tutorial Activity)
- Hurdle
- Mode
- Written
- Category
- Quiz
- Weight
- 25%
- Due date
LBRT #3 (1st attempt) 7/11/2024 - 8/11/2024
LBRT #3 (1st attempt) 12/11/2024 - 13/11/2024
The LBRT first attempt opens at 9am and closes at 4pm.
The LBRT optional second attempt opens at 9am and closes at 4pm.
- Learning outcomes
- L01, L02, L03, L04, L05
Task description
LBRT #3 will involve solving problems based on the learning materials covered in Weeks 9 to 12 inclusively. This includes all learning materials presented in Lectures 9 to 12, the associated tutorials, as well as CML5 and CML6. All answers must be entered into Blackboard by the due date and time.
LBRTs evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
See Additional Assessment Information.Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
Grade | Cut off Percent | Description |
---|---|---|
1 (Low Fail) | 0% - 29% |
Absence of evidence of achievement of course learning outcomes. |
2 (Fail) | 30% - 46% |
Minimal evidence of achievement of course learning outcomes. |
3 (Marginal Fail) | 47% - 49% |
Demonstrated evidence of developing achievement of course learning outcomes |
4 (Pass) | 50% - 64% |
Demonstrated evidence of functional achievement of course learning outcomes. |
5 (Credit) | 65% - 74% |
Demonstrated evidence of proficient achievement of course learning outcomes. |
6 (Distinction) | 75% - 84% |
Demonstrated evidence of advanced achievement of course learning outcomes. |
7 (High Distinction) | 85% - 100% |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
A student's final overall end of semester percentage mark will be rounded to determine their final grade. For example, 64.5% rounds to 65%, while 64.4% rounds to 64%.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
To successfully pass ECON1310, a student needs to achieve all three of the following requirements:
1. Receive a combined total assessment mark of at least 50 marks out of 100 marks from their CMLs Quizzes (25 marks available) and LBRTs (75 marks available).
2. Receive at least 10 marks out of 25 marks from their best 5 out of 6 CML Quizzes (each being worth 5 marks).
3. Receive at least 30 marks out of 75 marks from their LBRTs (each being worth 25 marks).
In determining a student's final overall grade for the course, the following will apply:
- If the CML Quizzes aggregate final mark is less than 10/25 and the LBRTs aggregate final mark is less than 30/75, the maximum possible grade will be 2.
- If the CML Quizzes aggregate final mark is less than 10/25 or the LBRTs aggregate final mark is less than 30/75, the maximum possible grade will be 3.
Details regarding the two assessable items (CML Quizzes and LBRTs) are outlined below.
CML Quizzes
- For step by step instructions on accessing, completing and submitting all CML quizzes, please refer to the course Blackboard site under Assessment > CML Quizzes > CML Administrative Folder.
- A student's best 5 out of 6 CML quizzes will be used in calculating the aggregate result that contributes to a student's overall mark.
- An optional second attempt is given for each CML quiz (except CML6 which has only one attempt). Each CML quiz opens and closes on the dates and times shown above. If only one attempt is submitted and a score received for a CML quiz, either the first attempt or just the second attempt, that quiz score will contribute towards the student's aggregate CML quiz result. If both the first and second attempts are submitted, the student's best score from the 2 attempts for a CML quiz will contribute towards their aggregate CML quiz result.
- CML quizzes evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
LBRT Problem Sets
- For step by step instructions on accessing, completing and submitting all LBRTs on Blackboard, please refer to the course Blackboard site under Assessment > LBRTs (Lecture Block Review Tasks).
- An optional second attempt is given for each LBRT. Each LBRT opens and closes at the dates and times shown above. If only one attempt is submitted and a score received for an LBRT, either the first attempt or just the second attempt, that LBRT score will contribute towards the student's aggregate LBRT result. If both the first and second attempts are submitted, the student's best score from the 2 attempts for a LBRT will contribute towards their aggregate LBRT result.
- All 3 LBRTs will be used in calculating the aggregate result that contributes to a student's overall mark. Details relating to the LBRT weighting breakdowns can be found below under the heading "IVA during Tutorial 8 and Tutorial 12 - Assessable Tutorial Discussion Activity."
- LBRTs evaluate students’ abilities, skills and knowledge without the aid of Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Plagiarism: The School of Economics is committed to reducing the incidence of plagiarism. Further information on plagiarism and how to avoid an allegation of plagiarism is available in this course profile under Policies & Guidelines. Please refer to the link to the Academic Integrity Module (AIM). It is strongly recommended that you complete the AIM ᅠif you have not already done so.
Identity Verified Assessment (IVA)
Purpose: Regular attendance and active participation during tutorials helps support your learning. It also allows tutors to get to know you, which in turn helps them to review and support your work in tutorials and assessment tasks (CMLs, LBRT Problem Sets). Importantly, it also allows tutors to identify if any students are struggling so that additional support can be provided when needed. This means tutors will be well placed toward the end of the semester to understand your level of work and to help maintain academic standards.
IVA during Tutorial 8 and Tutorial 12 - Assessable Tutorial Discussion Activity
During tutorials 8 and 12, an assessable Tutorial Discussion Activity will be conducted. During these tutorials, you will be asked to write down and verbally explain the solution to a question(s), based on material covered by LBRT #1 and LBRT #2 problem sets respectively, to your peers. The purpose of this is for students to demonstrate their understanding of what they have learned in the course by communicating with peers. This contributes towards one of the courses key learning objectives to “communicate statistical findings for practical and professional use.” The IVA Tutorial Activity marking rubric can be accessed via the course Blackboard site under the Assessment tab. The IVA Tutorial Activity is graded on a pass or fail basis.
Students will be required to attend their allocated tutorial and actively take part in both Tutorial Discussion Activities in tutorials 8 and 12. These two tutorials form an integral part of the assessment for LBRT #1 and LBRT #2 problem set marks (i.e. in effect, both tutorials 8 and 12 take the form of an “in class exam” which all students are required to complete. You MUST attend the “in class exam” to receive an LBRT mark). Please pay particular attention to ensure that you will be available to attend your allocated tutorial to complete all IVA Tutorial Discussion Activities during the semester. Not attending an IVA activity can impact your final grade. Students are not permitted to attend a tutorial that they did not sign on to for an IVA discussion activity.
Note that each LBRT problem set is worth 25%. Each LBRT mark in Blackboard will be scaled back to be out of 25% in order to finalise a student’s grade. Each LBRT problem set final mark is made up of two components: 50% comes from the student's LBRT mark after submitting the online problem set answers in Blackboard, with the other 50% of the LBRT mark for the online problem set answers in Blackboard only awarded after passing the Tutorial Discussion Activity. That is, there is a 50/50 split of marks based on your Blackboard mark and then passing the IVA Tutorial Discussion Activity. Your initial problem set mark recorded in Blackboard for both LBRT #1 and LBRT #2 will remain provisional until you have successfully completed and passed the required Tutorial Discussion Activity. That is, if you pass the tutorial discussion activity, your initial marks on Blackboard after submitting your LBRT attempts online will become your confirmed marks. If you do not attend and complete the second part of the LBRT task involving the Tutorial Discussion Activity, you will not gain the other half of the marks allocated to passing the Tutorial Discussion Activity. As an example, consider a student completes LBRT #1 online and their best score on Blackboard was 15/30. To calculate the student's end of semester final grade, their Blackboard score (of 15/30) would first be scaled back to be out of 25 marks (being 12.5/25 in this example). The following adjustments will then apply:
- If the student attends and passes the IVA Tutorial Discussion Activity in tutorial 8, this outcome will be recorded in Blackboard under a column titled “Tutorial 8 IVA” with the letter P (indicating PASS). This will indicate to the student that their original best LBRT #1 mark (in the example of 15/30) becomes their confirmed LBRT #1 mark when calculating their final grade (which will become 12.5/25 when scaled).
- If the student attends and fails the IVA Tutorial Discussion Activity in tutorial 8, it will be recorded in Blackboard under a column titled “Tutorial 8 IVA” with the letter F (indicating FAIL). This will indicate to the student that they will lose 50% of their LBRT #1 mark shown on Blackboard. Their LBRT #1 mark shown in Blackboard (in the example of 15/30) would scale to 12.5/25, and then be reduced to 6.25/25 when calculating their final grade.
- If the student does not attend the IVA Tutorial Discussion Activity in tutorial 8, it will be recorded in Blackboard under a column titled “Tutorial 8 IVA” with the number 0 (indicating FAIL and score to be reduced to zero). This will indicate to the student that they will lose 100% of their LBRT #1 mark(s) shown on Blackboard. Their original LBRT #1 mark(s) would be reduced to 0/25 when calculating their final grade.
Details of the weighting breakdown for the LBRT #1 and LBRT #2 assessment tasks are summarised below (note that there is no Tutorial Discussion Activity required for LBRT #3):
LBRT Problem Set 1: 25% (50% allocated to initial Blackboard submission mark, 50% allocated to initial Blackboard submission mark for passing the IVA Tutorial Activity during Tutorial 8.)
LBRT Problem Set 2: 25% (50% allocated to initial Blackboard submission mark, 50% allocated to initial Blackboard submission mark for passing the IVA Tutorial Activity during Tutorial 12.)
LBRT Problem Set 3: 25% (100% allocated to initial Blackboard submission mark, no IVA Tutorial Activity.)
How will the Tutorial Discussion Activity work
During tutorial 8 and tutorial 12, students must attend their allocated tutorial. At the start of the tutorial, students will be directed to sit at particular table by their tutor. They must show their UQ student card as proof of identity at the start of the Tutorial Discussion Activity. If a student does not have their UQ student card, the UQ Examinations Procedure Part F on student cards for examinations will apply. The use of Artificial Intelligence (AI) tools will not be permitted during the activity. Any attempted use of AI may constitute student misconduct under the Student Code of Conduct.At the start of the tutorials 8 and 12, the tutor will provide each student with a Question Sheet. The Question Sheet will be a single A4 sheet of paper and have a series of questions based on material covered in the relevant LBRT problem setᅠ (i.e., LBRT #1 for tutorial 8, LBRT #2 for tutorial 12). A variety of different questions among students can be expected. Each student should write their name and student number at the top of their Question Sheet.A complete set of instructions and details will be posted on the course Blackboard prior to the Tutorial Discussion Activities.
What happens at the end of the Tutorial Discussion Activity?
Your tutor will collect each student’s Question Sheet. It is anticipated that most students’ observed performance during the Tutorial Discussion Activity will match their performance recorded on Blackboard for their LBRTs. Once the tutor reviews all students' Question Sheet working after the tutorial, and the marks are reviewed by the Course Lecturer, students will receive either a P, F or 0 on Blackboard. All students' marks will be released on the course Blackboard site at the same time, ideally in the week after the Tutorial Discussion Activity. Students will be advised by email when their marks are available. Note that the marks will indicate the following:
- P = passed the Tutorial Discussion Activity of the relevant LBRT #1 or LBRT #2. In this case, the provisional mark on Blackboard can then be taken by students as confirmed (which will include the IVA Tutorial Discussion Activity weighting) for determining the student's final grade at the end of the course.
- F= failed the Tutorial Discussion Activity of the relevant LBRT #1 or LBRT #2 based on tutor observations during the tutorial. In this anticipated unlikely event, three outcomes are possible. First, the student can accept the failed decision and their relevant LBRT #1 or LBRT #2 mark in Blackboard will be reduced by 50% when determining the student's final grade at the end of the course. Second, the student can appeal the failed decision to the Course Lecturer who will be able to conduct an oral interview with the student to evaluate if their interview observed performance matches their relevant LBRT assessment performance. A student must email the Course Lecturer no later 11:59pm (AEST) on the 4th calendar day after the release of the grades on Blackboard (not counting the day grades are released) to be eligible for an interview. No interview will be possible after this time. Students should expect to explain the answers to a series of questions similar to those relating to the relevant LBRT assessment. The interview could be expected to last about 15-30 minutes, and will be conducted and recorded on Zoom (see UQ Assessment Procedure Part F (89) which states: “the performance will be recorded and retained in accordance with Appendix 1”). This will provide a student with another opportunity to pass the Tutorial Discussion Activity. Third, if the student appeals and then does not satisfy the Course Lecturer and fails their oral interview, the Course Lecturer will need to report the student to the School of Economics Academic Integrity Officer where further penalties may be imposed.
- 0 = did not attend the Tutorial Discussion Activity for the relevant LBRT #1 or LBRT #2. In this case, the mark initially recorded in Blackboard for a student’s LBRT attempt (including both attempts if submitted) will be reduced to 0 marks for the LBRT (an outcome that would have resulted if a student had failed to attend an exam) when determining the student's final grade at the end of the course.
What happens if you can’t attend the tutorial discussion activities (for Tutorials 8 and 12)
- Any requests for an extension must be made following the UQ assessment extension request process. It will require inclusion of valid supporting documentation, such as a medical certificate. Without an approved extension, being late for a required Tutorial Discussion Activity relating to an LBRT in Tutorial 8 or 12 will be considered as having failed to attend and a penalty imposed as noted above.
- Additional tutorials to complete the Tutorial Discussion Activity for students with an approved extension will be scheduled and advised (if needed) during the semester.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
Recommended Textbook
Black et al. (2016), Australasian Business Statistics, 4th Edition, Wiley Australia.
Hard copies of the textbook are available for purchase from bookshops and most online retailers should students wish to do so. Alternatively, convenient options are available to purchase an e-text version of the textbook here and here.
School of Economics Learning Resources
For assessment in this course students will be permitted to use Casio FX82 series (82 with any letters) or university approved (labelled) calculators.
Calculator requirements may differ for other university courses and students should check each course profile for the specific requirements.
PLEASE NOTE: It is the student’s responsibility to ensure they have the correct calculator prior to assessment in each of their courses. Guidelines for correct referencing techniques can be found in https://guides.library.uq.edu.au/referencing?b=g&d=a&group_id=15017.
Other Learning Resources & Information
The following additional information is available on Blackboard:
- Computer Managed Learning (CML) informationᅠ(under Assessment > CML Quizzes > CML Administrative Folder).ᅠ
- Lecture Block Review Tasks (LBRTs) information (under Assessment > LBRTs - Lecture Block Review Tasks).
- Identity Verified Assessment (IVA) tutorial activities information (under Assessment > Identity Verified Assessment (IVA) materials).
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
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Learning period | Activity type | Topic |
---|---|---|
Week 1 (22 Jul - 28 Jul) |
Lecture |
Lecture 1: Descriptive Statistics 1 statistical concepts and definitions; data types, sources, levels; descriptive & inferential statistics; sampling methods and errors. Learning outcomes: L01, L02, L03, L04, L05 |
Week 2 (29 Jul - 04 Aug) |
Lecture |
Lecture 2: Descriptive Statistics 2 Measures of central tendency, variation and shape for ungrouped data; box and whisker plot; linear combination of random variables; coefficient of correlation. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 1: Descriptive Statistics 1 Tutorial on work covered in Lecture 1. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 3 (05 Aug - 11 Aug) |
Lecture |
Lecture 3: Probability 1 Basic probability concepts, conditional probability. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 2: Descriptive Statistics 2 Tutorial on work covered in Lecture 2. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 4 (12 Aug - 18 Aug) |
Lecture |
Lecture 4: Probability 2 Discrete probability distributions, binomial probability. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 3: Probability 1 Tutorial on work covered in Lecture 3. Wednesday, August 14, is a Public Holiday. Therefore no tutorials or consultations will be held on that day. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 5 (19 Aug - 25 Aug) |
Lecture |
Lecture 5: Normal Distribution Understanding the basis of the normal distribution, interpreting the Standardised Normal Distribution table, computing Z - scores and finding probabilities. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 4: Probability 2 Tutorial on work covered in Lecture 4. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 6 (26 Aug - 01 Sep) |
Lecture |
Lecture 6: Sampling Distributions Sampling distributions of the mean and of the proportion. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 5: Normal Distribution Tutorial on work covered in Lecture 5. Practice IVA tutorial discussion activity at the start of tutorials (non-assessable but highly recommended to for all students to attend). Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 7 (02 Sep - 08 Sep) |
Lecture |
Lecture 7: Confidence Intervals 1 Confidence interval estimate for the mean using both Z and t distributions; confidence interval for proportion. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 6: Sampling Distributions Tutorial on work covered in Lecture 6. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 8 (09 Sep - 15 Sep) |
Lecture |
Lecture 8: Confidence Intervals 2 Sample size determination for the mean and proportion; confidence interval for the difference between two means. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 7: Confidence Intervals 1 Tutorial on work covered in Lecture 7. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 9 (16 Sep - 22 Sep) |
Lecture |
Lecture 9: Hypothesis Testing 1 Hypothesis testing methodology; one and two-tailed tests on the mean using critical value approach (Z and t); types of errors possible. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 8: Confidence Intervals 2 Tutorial on work covered in Lecture 8. IVA tutorial discussion activity (assessable) will be held at the start of the tutorial. All students should attend this assessable tutorial. Learning outcomes: L01, L02, L03, L04, L05 |
|
Mid Sem break (23 Sep - 29 Sep) |
No student involvement (Breaks, information) |
Mid-semester Break Please note, there will be no classes this week. |
Week 10 (30 Sep - 06 Oct) |
Lecture |
Lecture 10: Hypothesis Testing 2 p-value approach to hypothesis testing; test for proportion; pooled variance test for difference between two means. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 9: Hypothesis Testing 1 Tutorial on work covered in Lecture 9. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 11 (07 Oct - 13 Oct) |
Lecture |
Lecture 11: Simple Linear Regression 1 SLR model; equation estimation using Excel; coefficient of determination; standard error of the estimate; confidence interval for the slope. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 10: Hypothesis Testing 2 Tutorial on work covered in Lecture 10. Monday, October 7, is a Public Holiday. Therefore no tutorials or consultations will be held on that day. Students who normally attend a Monday tutorial session are welcome to attend an alternative tutorial session for this week only. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 12 (14 Oct - 20 Oct) |
Lecture |
Lecture 12: Simple Linear Regression 2 Assumptions; residual analysis; hypothesis test on slope. Learning outcomes: L01, L02, L03, L04, L05 |
Tutorial |
Tutorial 11: Simple Linear Regression 1 Tutorial on work covered in Lecture 11. Learning outcomes: L01, L02, L03, L04, L05 |
|
Week 13 (21 Oct - 27 Oct) |
Lecture |
Lecture 13: Review Review of content from Lectures 1 - 13. |
Tutorial |
Tutorial 12: Simple Linear Regression 2 Tutorial on work covered in Lecture 12. IVA tutorial discussion activity (assessable) will be held at the start of the tutorial. All students should attend this assessable tutorial. Learning outcomes: L01, L02, L03, L04, L05 |
Additional learning activity information
ECON1310 is a #2 unit course. UQ's expectation is that a #2 unit course requires a time allocation of, on average, 10 hours per week. Lectures and tutorials account for about 3.5 hours per week. Therefore, it is expected that you will be spending a further 6.5 hours per week in self-directed learning. This ideally should include studying the lecture and tutorial materials in detail, completing the regular assessment tasks, attending consultation sessions, attempting questions in the textbook, etc. Please give serious consideration as to whether you are willing and able to make this time commitment before enrolling. Experience shows that students who do not put in this basic time allocation tend to struggle.
ECON1310 weekly face-to-face lectures will only be delivered on campus. In addition, ECON1310 lectures can be watched fully online through video recordings that will be made available on a purpose built Blackboard site. Face-to-face tutorial classes only will be delivered on campus will also be available each week. Studio produced video recordings of fully worked solutions to all tutorial questions will also be made available on a weekly basis during the semester. We recommend that you complete the material relating to all lectures and tutorials.
Ensure you attain the marks necessary to achieve the grade to which you aspire. We are aware that some students aspire to a grade of 6 or 7, whilst others aspire to a 4. All such aspirations are fine with us. Our job is to clearly specify the grade cut-offs, clearly state the marking criteria, and then mark assessments according to these criteria. In a very large course such as ECON1310, it is inevitable that some students will end up close to a grade cut-off. This is not unusual or unfair. You control your own destiny, so it is up to you to ensure you are on the right side of a grade cut-off. Missing out on a grade cut-off by a small amount is not grounds for a re-mark or any special consideration. Assessment results will only be revisited if a marking error has occurred (e.g. assessment has not been graded according to the stated marking criteria), or if an administrative error has occurred (e.g. results for individual assessment pieces have not been added up correctly). Marks for assessment tasks are released regularly throughout the semester. Students should check their marks as soon as they are released. If you feel a marking error has occurred, please contact the CML Coordinator at cml.1310@uq.edu.au immediately. If the situation is not able to be resolved, the CML Coordinator will contact the Course Lecturer to make a decision. After each assessable item, students will be given the opportunity to review their assessment marks to satisfy themselves that a marking or administrative error has not occurred.
Make sure you check your student email and the ECON1310 Blackboard site regularly. All important correspondence will be communicated to students throughout the semester by email and/or via Blackboard.
Lectures
During the semester, lectures, lecture notes and lecture videos (which can be viewed online anytime after release) will be available before the actual face-to-face lecture on campus. Weekly lecture videos have been edited into 5 to 10 minute segments. The video material will be similar to what will be delivered in the weekly face-to-face lectures. The lecture videos will available on the purpose built ECON1310 Blackboard site. It is intended to make the Blackboard site available to all students prior to the start of the course. In particular, all learning materials for Lecture 1 will become available to students to allow them to become familiar with the Blackboard site. Students should take the opportunity to watch some of the video segments for Lecture 1.
Tutorials
Tutorials will commence in Week 2 and be 1 hour and 20 minutes duration. All tutorials in any given week cover the same questions and are based on material presented in the previous teaching week's lecture.
Tutorials play a very important role in this course. Students must sign on to a tutorial at the start of the semester and will only be permitted to attend that tutorial during the semester. Students are not allowed to swap tutorials after census date. They are a student's main opportunity to seek individual assistance and further explanation from teaching staff regarding any areas of the subject. Tutorial questions will be posted on the course Blackboard site throughout the semester. Most tutorials work through a series of pre-set questions. You should aim to work through the tutorial material before going to the tutorial so as to get the most out of each tutorial. Do not expect your tutor to simply provide you with the answers. This is not their job. The tutor will direct questions to students during the class and active participation is encouraged. In particular, getting to know your tutor and regularly participating in tutorials will greatly assist you in being able to meet and pass the requirements of the compulsory Identity Verified Assessment (IVA) Tutorial Discussion Activities - see Additional Assessment Information for details. Please pay particular attention to ensure that you will be available to attend your allocated tutorial to complete all IVA Tutorial Discussion Activities during the semester. Not attending an IVA activity can impact your final grade. Students are not permitted to attend a different tutorial, to what they sign on to at the start of the semester, for the IVA tutorial discussion activities.
Video demonstrated solutions to each tutorial question will be made available on Blackboard. The solutions are presented by a variety of experienced tutors and will only become available at the end of each tutorial week (see Blackboard for release dates and times).
Peer Assisted Study Sessions (PASS)
PASS is no longer offered by the School of Economics in ECON1310. However, video demonstrated solutions to weekly PASS question sheets from previous semesters will be made available on Blackboard to help support students' learning. See Blackboard for details.
Computer Managed Learning (CML) Quizzes
Online computer generated quizzes form part of the student's individual assessment in this course. CML quizzes also serve as a valuable learning tool for students, with lecture and tutorial materials able to be used to solve CML questions. The regular completion of these individual assessment quizzes will assist students in consolidating their learning while also providing valuable feedback on areas that may require more work. For example, students can learn from their mistakes by reworking questions marked as incorrect. The correct answers to questions will be made available online for each set of CML quiz questions, but only after the CML quiz has been submitted and the deadline for a CML quiz to be completed has expired. Students are able to also take a second optional attempt at the same CML quiz (which has a different set of questions to the first attempt, and much less time to complete it) in order to improve their first attempt mark. The best score, from the two attempts for each CML quiz will contribute towards a student's aggregate CML quiz assessment mark. If a student completes only one of the two possible attempts, the mark from the completed attempt will contribute toward the student's aggregate CML quiz assessment mark. For a complete description regarding the CML quizzes, please read the Assessment Section of this Course Profile. For instructions on completing and submitting a CML quiz, please refer to the course Blackboard site under Assessment.
Note: In CML2 to CML6, some revision questions will be included based on questions from any previous CML quiz. These revision questions will be in addition to the main topics indicated in Assessment Details.
Lecture Block Review Task (LBRT) Problem Sets
These are another form of online quiz that form part of the student's individual assessment in the course. They too, like CMLs, aim to provide regular student feedback at key points during the course. By breaking the course into a three distinct blocks, each covering four weeks of learning materials (rather than two weeks as in CMLs), LBRTs allow students ongoing opportunities to self-evaluate, monitor and improve their performance in a timely manner before progressing to the next stages within the course. LBRTs involve problem solving that draw on relevant learning materials from lectures, tutorials and CML quizzes. They serve to provide timely assessment to support student learning rather than large stake assessments (like a highly weighted final exam at the end of the course). Therefore, LBRTs aim to motivate students to remain engaged with their learning by supporting them in managing the cumulative nature of the learning needed to do well in the course. LBRTs are delivered through Blackboard and use the same format and rules as CML quizzes. There are three (3) LBRTs required to be completed by students during the course. Each LBRT has an optional second attempt that will be available after the first attempt closes. For a complete description regarding the LBRTs, please read the Assessment Section of this Course Profile. For instructions on completing and submitting a LBRTs, please refer to the course Blackboard site under Assessment.
Consultation
Consultation is your chance to speak directly with the teaching staff (tutors and the Course Lecturer). A consultation timetable listing the consultation times and locations of teaching staff will be posted on the Blackboard site under Course Help. There is no need to make an appointment for consultation and you may attend any teaching staff's consultation session. Note that consultation sessions may be busy prior to the CML quiz deadlines or submission of the LBRTs.
Don't be shy to seek out one-on-one help from teaching staff during consultation sessions. They are there to help. Note, however, that staff on consultation will expect that you have been performing your side of the bargain, that is, dedicating 10 hours per week to ECON1310 by reviewing the lecture material, attending tutorials, watching content videos, and so on. If it becomes obvious that you have not, you may be asked to return when you have done so.
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.