Aims: To introduce students to the principles of data analysis with particular reference to business applications.
Learning Outcomes: Students should be able to search for and download data from the web; convert raw data into index numbers or percentages; classify data by level (nominal, ordinal, interval, ratio); identify dependent and independent variables; and carry out parametric statistical tests. They should also be able to carry out elementary project appraisal techniques such as simple Decision Trees and Discounted Cash Flow analysis.
Skills:
* Intellectual: identify the correct technique required to solve data analysis problems. Taught and assessed.
* Professional: apply statistical techniques to business problems. Taught and assessed.
* Key skills: use and understanding of numerical data. Taught and assessed.
Content: Collection and presentation of data; descriptive statistics; inferential statistics including correlation and regression; index numbers; time series; elementary probability; decision trees.
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