The main aim of this unit is to develop the analytical, mathematical and statistical skills of learners in order to improve their approach to solving problems or analysing and evaluating numerical information resulting from the research or surveys.
Upon successful completion of the course students will be able to:
Learning and teaching methods/strategies used to enable the achievement of learning outcomes:
Learning takes place on a number of levels through lectures, class discussion including problem review and analysis. Formal lectures provide a foundation of information on which the student builds through directed learning and self managed learning outside of the class. The students are actively encouraged to form study groups to discuss course material which fosters a greater depth learning experience.
Relevant experience is taken into consideration for students 21 years of age and over who have not completed any formal qualifications.
Surveys and presentation of information. Published statistics. Primary and secondary data. Questionnaires. Sampling: choice of sample, sampling frame, random sampling, systematic sampling, stratified sampling, multi-stage sampling, quota sampling, cluster sampling, sample size, bias.
Frequency distributions. Tables, charts, discrete and continuous variable, grouped and ungrouped frequency distributions, visual displays, bar charts, line charts, pie charts, Gantt charts, histograms, graphs, scatter graphs, Z-charts.
Statistical measures: the arithmetic mean. The arithmetic mean of grouped data. The media. The mode When to use the mean, median and mode. Quartiles. Quartile deviations. Standard deviations. Skewness. Measuring the degree of skewness.
The J -Curve.
Regression and correlation: calculating and interpreting the regression line. Method of Least Squares. The correlation coefficient. Rank correlation. Interpretation and use of the correlation co-efficient.
Time series Analysis: seasonal and cyclical variations, trends, moving averages and forecasts. Index numbers: index relatives, price indices and quantity indices. Lespeyre and Paasche methods. Composite index numbers. Retail Price Index (UK) and Stock Exchange Indices.
Essential principles of probability. Additional laws of probability. Multiplication laws. Tree diagrams. Mutually exclusive events.
Essentials Quantitative Methods for Business, Management and Finance
L. Oakshott (Palgrave)
Quantitative Approaches in Business Studies C. Morris (FT Prentice Hall)
Tutorial support includes feedback on assignments and may vary by college according to local needs and wishes.
Advance reading and preparation / Class preparation / Background reading / Group study / Portfolio / Diary etc
Working through the course text and completing assignments as required will take up the bulk of the learning time. In addition students are expected to engage with the tutor and other students and to undertake further reading using the web and/or libraries.
Final Examination: 70%
Coursework: 30%
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