This course will introduce students to basic methods of empirical enquiry into Accounting, Finance and Management. The course will provide a solid foundation in statistical inference, enabling the student to become a competent producer of basic statistical research.
Module will run
Occurrence
Teaching period
A
Spring Term 2022-23 to Summer Term 2022-23
Module aims
This course will introduce students to basic methods of empirical enquiry into Accounting, Finance and Management. The course will provide a solid foundation in statistical inference, enabling the student to become a competent producer of basic statistical research. In addition the skills acquired will enable the student to become a somewhat more sophisticated consumer of more advanced research methodologies. It is also designed for students to appreciate the advantages and limitations of quantitative techniques.
Module learning outcomes
Understand the detailed technical nature of quantitative techniques
Appreciate and select from the different quantitative procedures used in the analysis of different data types
Use computer packages for data analysis and interpret their output
Module content
Topic 1 – Measures and Charts
Types of data (nominal, ordinal, discrete, continuous)
Central tendency (mean, median and mode)
Measures of spread (variance, standard deviation, IQR, range, coefficient of variation)
Graphical and tabular presentation of different types data
Topic 2 – Price Indices
Relative changes in price
Inflation
Simple and aggregate
Correction for inflation
Topic 3 – Probability
Basic and conditional probability (independence, mutual exclusivity)
Frequency tables
Bayes’ Theorem
Topic 4 – Statistical Distributions
Concept of sampling distributions
Ubiquity of normal distribution
Computations involving probability and proportions using the standard tables.
Topic 5 – Sampling with Confidence
Methods of sampling
Concept of estimation and controlled errors
The Central Limit Theorem
Construction and interpretation of confidence intervals, both 1 and 2 tailed
Determining sample size
Topic 6 – Basic Hypothesis Testing
Null and alternate hypotheses
False positives and false negatives
Comparison of mean with estimate, of two means and of paired data
Topic 7 – ANOVA
Need for ANOVA
Calculation and interpretation of ANOVA
Topic 8 – Chi-squared
Two types of chi-squared test
Calculation and interpretation of chi-squared test
Topic 9 – Correlation and Regression
Causality vs correlation
Pearson’s correlation coefficient
Interpretation of simple linear regression
Indicative assessment
Task
% of module mark
Closed/in-person Exam (Centrally scheduled)
30
Essay/coursework
70
Special assessment rules
None
Indicative reassessment
Task
% of module mark
Essay/coursework
100
Module feedback
Feedback on the summative exam will be available after the exam has been marked; in early summer term
Feedback on the essay/assignment will be available after marking has been completed.
Feedback on the formative quizzes will be available immediately after submission of answers, but also in seminars if requested.