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This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.
Please note that given the circumstances of COVID-19, there may be some modifications to the assessment schedule promoted in Handbook for Semester 1 2020 Units. Students will be notified of all approved modifications by Unit Coordinators via email and Unit Blackboard sites. Where changes have been made, these are designed to ensure that you still meet the unit learning outcomes in the context of our adjusted teaching and learning arrangements.
In this unit students will identify and implement appropriate statistical procedures to assist managers in making sound decisions in the face of uncertainty. The unit initially concentrates on developing an understanding of averages, variability and probability along with the various models of data behaviour in business enabling managers to choose between different investment strategies. From here the students learn the different methods of sampling, and an understanding of inferential statistics and an appreciation of estimates of the population parameters is established through confidence intervals. This leads to the main themes of the unit including hypothesis testing of means, proportions, variances and categorical responses and finally regression and multiple regression analysis. These techniques are used to authenticate the model, and to estimate and predict with confidence future outcomes for business. These applications are all applied to real data sets.
On completion of this unit students should be able to:
Students will attend on campus classes as well as engage in learning activities through ECU Blackboard.
| Joondalup | Mount Lawley | South West (Bunbury) | |
|---|---|---|---|
| Semester 1 | 13 x 2 hour seminar | Not Offered | Not Offered |
| Semester 2 | 13 x 2 hour seminar | Not Offered | Not Offered |
For more information see the Semester Timetable
Students will engage in learning experiences through ECU Blackboard as well as additional ECU learning technologies.
On-campus students attend lectures and seminars using a technology enhanced learning (TEL) learning approach including interactive presentations, videos, small group and individual activities in class and online. Students are required to complete a series of tasks allocated each week before attending weekly seminars. On campus activities will focus on theoretical and practical issues, data analysis, problem solving, critical thinking and teamwork. Seminars provide students with the opportunity to consolidate the key concepts of the unit and guide students through the theoretical and practical issues and data analysis. Online students participate in the unit via Blackboard and will require regular online access. Students are required to work through a series of tasks and participate in various online activities every week, to learn to problems solve, to analyse, to discuss, to develop and to apply the concepts covered in lectures, readings, and assessments. Online activities are designed to develop the students’ problem solving skills, critical thinking and teamwork skills. Assessment tasks are designed to allow students to demonstrate their capacity to work in teams, to problem solve and to think critically when applying statistical concepts and knowledge.
GS1 GRADING SCHEMA 1 Used for standard coursework units
Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant Board of Examiners.
| Type | Description | Value |
|---|---|---|
| Exercise | Weekly pre-class work | 15% |
| Test | Online tests | 15% |
| Assignment | Group assignment | 20% |
| Examination | Final examination | 50% |
| Type | Description | Value |
|---|---|---|
| Exercise | Weekly pre-class work | 15% |
| Test | Online tests | 15% |
| Assignment | Group assignment | 20% |
| Examination | Final examination | 50% |
For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.
Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:
Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.
The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.
ECF6102|4|1
This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.
Please note that given the circumstances of COVID-19, there may be some modifications to the assessment schedule promoted in Handbook for this unit. All assessment changes will be published by 27 July 2020. All students are reminded to check handbook at the beginning of semester to ensure they have the correct outline.
In this unit students will identify and implement appropriate statistical procedures to assist managers in making sound decisions in the face of uncertainty. The unit initially concentrates on developing an understanding of averages, variability and probability along with the various models of data behaviour in business enabling managers to choose between different investment strategies. From here the students learn the different methods of sampling, and an understanding of inferential statistics and an appreciation of estimates of the population parameters is established through confidence intervals. This leads to the main themes of the unit including hypothesis testing of means, proportions, variances and categorical responses and finally regression and multiple regression analysis. These techniques are used to authenticate the model, and to estimate and predict with confidence future outcomes for business. These applications are all applied to real data sets.
On completion of this unit students should be able to:
Students will attend on campus classes as well as engage in learning activities through ECU Blackboard.
| Joondalup | Mount Lawley | South West (Bunbury) | |
|---|---|---|---|
| Semester 1 | 13 x 2 hour seminar | Not Offered | Not Offered |
| Semester 2 | 13 x 2 hour seminar | Not Offered | Not Offered |
For more information see the Semester Timetable
Students will engage in learning experiences through ECU Blackboard as well as additional ECU learning technologies.
On-campus students attend lectures and seminars using a technology enhanced learning (TEL) learning approach including interactive presentations, videos, small group and individual activities in class and online. Students are required to complete a series of tasks allocated each week before attending weekly seminars. On campus activities will focus on theoretical and practical issues, data analysis, problem solving, critical thinking and teamwork. Seminars provide students with the opportunity to consolidate the key concepts of the unit and guide students through the theoretical and practical issues and data analysis. Online students participate in the unit via Blackboard and will require regular online access. Students are required to work through a series of tasks and participate in various online activities every week, to learn to problems solve, to analyse, to discuss, to develop and to apply the concepts covered in lectures, readings, and assessments. Online activities are designed to develop the students’ problem solving skills, critical thinking and teamwork skills. Assessment tasks are designed to allow students to demonstrate their capacity to work in teams, to problem solve and to think critically when applying statistical concepts and knowledge.
GS1 GRADING SCHEMA 1 Used for standard coursework units
Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant Board of Examiners.
| Type | Description | Value |
|---|---|---|
| Exercise | Weekly pre-class work | 15% |
| Test | Online tests | 15% |
| Assignment | Group assignment | 20% |
| Exercise | Final assessment | 50% |
| Type | Description | Value |
|---|---|---|
| Exercise | Weekly pre-class work | 15% |
| Test | Online tests | 15% |
| Assignment | Group assignment | 20% |
| Exercise | Final assessment | 50% |
For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Access and Inclusion website.
Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:
Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.
The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.
ECF6102|4|2