To achieve the grade 12, students should meet the
following learning objectives with no or only minor mistakes or
errors: At the end of the course you should be able to:
- Identify different types of quantitative data and explain basic
methods of data collection and experimental design
- Use and critically evaluate the use of graphics, tables, and
summary measures to illustrate relationships in data, appropriate
for the purpose at hand,
- Use elementary theory of probability and distributions to
calculate sample distributions and the probabilities of alternative
outcomes and make basic statistical inferences (tests) about
population characteristics from samples,
- Use and interpret the output of methods to statistically
analyze associations, such as contingency tables and single and
multiple regression and recognize common problems and limitations
in such methods,
- When faced with a specific research question and available
data, select one or more appropriate statistical methods to address
the question, develop a structured and disciplined approach to
statistical analysis critically evaluate the
results.
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This course introduces you to basic quantitative skills in
business analysis, including methods for presenting and
characterizing quantitative data, making inferences from data based
on the theory of probability and statistics, using data to assess
relationships and effects, recognizing potential weaknesses or
pitfalls in quantitative analysis, and using data for business
decision making. The purpose of the course is to make you an
educated user of quantitative methods by introducing you to the
main theoretical concepts and issues, rather than giving you an
extensive training in the underlying statistical theory. Topics
include: data representation and summary measures; exploratory data
analysis, data collection and basic experimental design;
probability theory and distributions, sampling distributions,
confidence intervals, significance tests, contingency tables and
Bayesian inference, analysis of proportions, and single and
multivariate regression analysis.
Integration: The course provides the essential skills required for
quantitative business analysis, with an emphasis on conceptual
understanding and critical skills rather than on the practicalities
of data collection. The latter will be introduced immediately after
the course ends, in the context of the first-year project, where
students will get a first opportunity to use the techniques in
realistic settings. The emphasis in the course on the tools of
quantitative analysis is complemented by the course in
Interdisciplinary Research Methods, which focuses on the
philosophical underpinnings underlying statistical approaches,
notions of construct validity, questionnaire design, and other
broader methodological issues.
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Michael Barrow, Statistics for Economics, Accounting and
Business Studies, 6e, Pearson Education, 2014, with online course
material access. ISBN: 97802737
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