ETF5912 - Data analysis in business - 2019

This unit will introduce statistical concepts and their applications to business sectors of finance, accounting, marketing and management. Topics covered include: sampling techniques, confidence intervals and hypothesis testing (for both single populations and between populations). The multiple regression models and time series models -- that are very popular in data analysis and forecasting in public sectors and industries -- will be covered in detail in this unit.

The learning goals associated with this unit are to:

1. define different sampling techniques and use Excel to generate samples from these techniques
2. demonstrate an understanding of the role of inference and hypothesis testing in statistics and their value when applied in financial, marketing and management fields
3. conduct hypothesis tests for means and proportions of single populations, identify significant differences between two populations in terms of means, proportions and variances and interpret the value of these techniques in business
4. interpret and analyse the results of a regression analysis using a linear model, a model which incorporates dummy variables, or models involving nonlinear terms.

Within semester assessment: 40% + Examination: 60%

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.

See also Unit timetable information