School: Business and Law

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.

  • Unit Title

    Quantitative Skills for Business
  • Unit Code

    ECF6102
  • Year

    2021
  • Enrolment Period

    1
  • Version

    4
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr Anna GOLAB

Description

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.

Learning Outcomes

On completion of this unit students should be able to:

  1. Solve authentic business problems, by critically thinking about processes and assumptions within the Industry.
  2. Develop effective communication and effective teamwork skills to solve business problems by integrating theory with practice, and reflecting on individual and group performance.
  3. Apply statistical thinking, concepts and techniques to the daily business decision-making process.
  4. Generate solutions using a statistical software package to interpret statistical output, and predict future trends from the analysis.

Unit Content

  1. Introduction to statistical concepts.
  2. Review of measures of central tendency and variation.
  3. Analysis of skewness and relative dispersion.
  4. General probability concepts and probability distributions.
  5. Sampling distributions for both small and large samples.
  6. Discrete & continuous probability models in business behaviour.
  7. Point and interval estimation of population parameters.
  8. Hypothesis testing for means, proportions & variances.
  9. Two sample tests - confidence intervals and hypothesis tests for - comparing means for two independent populations, two related populations, and comparing proportions.
  10. Determining cause and reliable forecasting with correlation and regression analysis. Testing & inference of parameters.
  11. Multiple regression analysis.
  12. Non parametric analysis for categorical variables.
  13. Analysis of all topics using real data and appropriate computer software.

Learning Experience

ON-CAMPUS

Students will attend on campus classes as well as engage in learning activities through ECUs LMS

JoondalupMount LawleySouth West (Bunbury)
Semester 113 x 2 hour seminarNot OfferedNot Offered
Semester 213 x 2 hour seminarNot OfferedNot Offered

For more information see the Semester Timetable

ONLINE

Students will engage in learning experiences through ECUs LMS as well as additional ECU l

Additional Learning Experience Information

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.

Assessment

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 School Progression Panel.

ON CAMPUS
TypeDescriptionValue
ExerciseWeekly pre-class exercise15%
TestOnline tests15%
AssignmentAssignment20%
ExaminationEXAM50%
ONLINE
TypeDescriptionValue
ExerciseWeekly pre-class exercise15%
TestOnline tests15%
AssignmentAssignment20%
ExaminationEXAM50%

Core Reading(s)

  • M.Berenson, D. L., & K. Szabat, D. S. (2019). Basic Business Statistics, Global Edition (14th ed.). Harlow, United Kingdom: Pearson. Retrieved from https://ebookcentral.proquest.com/lib/ecu/detail.action?docID=5731467
  • M.Berenson, D. L., & K. Szabat, D. S. (2019). Basic Business Statistics, Global Edition (14th ed.). Harlow, United Kingdom: Pearson. Retrieved from https://ebookcentral.proquest.com/lib/ecu/detail.action?docID=5731467
  • M.Berenson, D. L., & K. Szabat, D. S. (2019). Basic Business Statistics, Global Edition (14th ed.). Harlow, United Kingdom: Pearson. Retrieved from https://ebookcentral.proquest.com/lib/ecu/detail.action?docID=5731467

Disability Standards for Education (Commonwealth 2005)

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.

Academic Misconduct

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:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

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

School: Business and Law

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.

  • Unit Title

    Quantitative Skills for Business
  • Unit Code

    ECF6102
  • Year

    2021
  • Enrolment Period

    2
  • Version

    4
  • Credit Points

    20
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Coordinator

    Dr Anna GOLAB

Description

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.

Learning Outcomes

On completion of this unit students should be able to:

  1. Solve authentic business problems, by critically thinking about processes and assumptions within the Industry.
  2. Develop effective communication and effective teamwork skills to solve business problems by integrating theory with practice, and reflecting on individual and group performance.
  3. Apply statistical thinking, concepts and techniques to the daily business decision-making process.
  4. Generate solutions using a statistical software package to interpret statistical output, and predict future trends from the analysis.

Unit Content

  1. Introduction to statistical concepts.
  2. Review of measures of central tendency and variation.
  3. Analysis of skewness and relative dispersion.
  4. General probability concepts and probability distributions.
  5. Sampling distributions for both small and large samples.
  6. Discrete & continuous probability models in business behaviour.
  7. Point and interval estimation of population parameters.
  8. Hypothesis testing for means, proportions & variances.
  9. Two sample tests - confidence intervals and hypothesis tests for - comparing means for two independent populations, two related populations, and comparing proportions.
  10. Determining cause and reliable forecasting with correlation and regression analysis. Testing & inference of parameters.
  11. Multiple regression analysis.
  12. Non parametric analysis for categorical variables.
  13. Analysis of all topics using real data and appropriate computer software.

Learning Experience

ON-CAMPUS

Students will attend on campus classes as well as engage in learning activities through ECUs LMS

JoondalupMount LawleySouth West (Bunbury)
Semester 113 x 2 hour seminarNot OfferedNot Offered
Semester 213 x 2 hour seminarNot OfferedNot Offered

For more information see the Semester Timetable

ONLINE

Students will engage in learning experiences through ECUs LMS as well as additional ECU l

Additional Learning Experience Information

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.

Assessment

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 School Progression Panel.

ON CAMPUS
TypeDescriptionValue
ExerciseWeekly pre-class exercise15%
TestOnline tests15%
AssignmentAssignment20%
ExaminationEXAM50%
ONLINE
TypeDescriptionValue
ExerciseWeekly pre-class exercise15%
TestOnline tests15%
AssignmentAssignment20%
ExaminationEXAM50%

Core Reading(s)

  • M.Berenson, D. L., & K. Szabat, D. S. (2019). Basic Business Statistics, Global Edition (14th ed.). Harlow, United Kingdom: Pearson. Retrieved from https://ebookcentral.proquest.com/lib/ecu/detail.action?docID=5731467
  • M.Berenson, D. L., & K. Szabat, D. S. (2019). Basic Business Statistics, Global Edition (14th ed.). Harlow, United Kingdom: Pearson. Retrieved from https://ebookcentral.proquest.com/lib/ecu/detail.action?docID=5731467

Disability Standards for Education (Commonwealth 2005)

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.

Academic Misconduct

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:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students' work;

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