| Effective Term: | 2024/05 |
| Institute / School : | Institute of Innovation, Science & Sustainability |
| Unit Title: | Business Statistics |
| Unit ID: | BUGEN1502 |
| Credit Points: | 15.00 |
| Prerequisite(s): | Nil |
| Co-requisite(s): | Nil |
| Exclusion(s): | Nil |
| ASCED: | 080301 |
| Other Change: | |
| Brief description of the Unit |
This course enables students to develop an understanding of the role of statistics in business and research and develop foundational knowledge and skills in the appropriate use of a range of statistical techniques. The course introduces spreadsheeting with an emphasis on the use of Excel as a statistical tool. Students develop core knowledge and applied skills in the following areas: descriptive statistics, elementary probability, discrete and continuous probability distributions, statistical inference, simple linear regression and correlation, forecasting and time series and index numbers. |
| Grade Scheme: | Graded (HD, D, C, P, MF, F, XF) |
| Work Experience Indicator: |
| No work experience |
| Placement Component: | |
| Supplementary Assessment:Yes |
| Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment |
| Course Level: |
| Level of Unit in Course | AQF Level(s) of Course | | 5 | 6 | 7 | 8 | 9 | 10 | | Introductory | | |  | | | | | Intermediate | | | | | | | | Advanced | | | | | | |
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| Learning Outcomes: |
| Knowledge: |
| K1. | Describe a set of data using appropriate statistical measures and identify commonly used techniques for data collection and analysis. |
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| K2. | Describe the role of statistical analysis and probability for decision making. |
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| K3. | Recognise the role of hypothesis tests in statistics. |
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| K4. | Describe relationships between two variables using linear and time series regression equations. |
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| K5. | Define index numbers and time value of money. |
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| Skills: |
| S1. | Use Excel to perform routine data management tasks and statistical analyses. |
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| S2. | Present data in a clear and informative way in both tabular and graphical form. |
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| S3. | Perform hypothesis tests & construct confidence intervals for single means. |
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| S4. | Model the relationship between two variables using linear regression equations and time series techniques. |
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| S5. | Interpret and communicate the results from statistical analysis using appropriate statistical language and conventions. |
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| Application of knowledge and skills: |
| A1. | Interpret computer output in terms that relate to the particular problem situation. |
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| A2. | Select and perform appropriate statistical tests for given data sets and problem situations. |
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| Unit Content: |
•Data classification and terminology.
•Descriptive statistics.
•Computer analysis of data.
•Probability and probability distributions.
•Estimation and hypothesis testing.
•Linear regression and correlation.
•Index numbers and time series. |
| Graduate Attributes: |
| | Learning Outcomes Assessed | Assessment Tasks | Assessment Type | Weighting | | 1. | K1, K2, K4, S1, S2, S4, S5, A1, A2 | Apply appropriate statistical analysis and produce professional presentation and interpretation of qualitative and quantitative data based on a relevant business context. | Assignment | 20-30% | | 2. | K1, K2, K3, S1, S3, A1, A2 | Students demonstrate conceptual basis of a statistical technique, perform appropriate calculations or apply an appropriate statistical technique using computer software and interpret the results obtained in context. | Quizzes | 20-30% | | 3. | K1, K2, K5, S1, S5, A1, A2 | Final test/assessment | Final summative assessment | 40-50% |
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