The aim of this module is to provide students with a range of statistical approaches to sample data analysis, which are useful in applications related to management in social, economic and business related activity.

A.   Knowledge and Understanding

• Understand the context and assumptions behind the application of various statistical techniques;
• Understand the concept of probability theory, confidence interval estimation and hypothesis testing.
• Understand the principles of multivariate modelling and forecasting methods.
• Understand  and critically evaluate  the survey process as a method of data collection including its assumptions and limitations

B.      Intellectual Skills:

• Develop the ability to appreciate and assess empirical work, and therefore learn to apply the relevant statistical technique in the correct situation.
• Model problems quantitatively and understand and evaluate the evidence.
• Interpret quantitative solutions in their applied context.

C.      Discipline Specific Skills:

• Solve problems using statistical techniques based on probability theory, including population inference from sample data and hypothesis testing;
• Demonstrate the practice of multivariate modelling and the basic techniques of business forecasting;
• Evaluate the survey process, questionnaire design, specify aims and objectives, sampling frames, and sample size;     
• Utilise statistical software as an aid to problem solving.

D.      Transferable Skills:

• Work individually and independently on lecture and reference materials.
• Use statistical techniques and a software tool to record, display and analyse information
• Interpret statistical results and draw conclusion from them.

The module will be delivered through a mix of large & small group face-to-face sessions, including, where relevant, supporting digital learning activities and/or recordings

Formal, summative assessment is through examination.The examinations contain a range of questions designed to cover the learning outcomes for the modules and to test skill development. Questions set are not only designed to test students’ basic knowledge and comprehension of the syllabus, but also to assess their ability to apply such knowledge in particular contexts. They require a combination of numerical and written answers, which test students’ development of intellectual, communication, numeric and reasoning skills, as well as subject-specific knowledge.

Formative assessment is provided through class questions, occasionally marked by students themselves. Students are also encouraged to submit queries and answers to past examination papers for discussion and marking.

Probability and sampling distributions; Point and confidence interval estimation; Hypothesis testing and analysis of variance; Non-Parametric methods; Correlation analysis and regression; Multiple regression; Model building; Residual analysis; Forecasting methods and choice governing use of particular methods; Survey methods including specifying aims and objectives, sampling frames, sample design and size, questionnaire design, collection and analysis of data.