Course Title: Business Statistics
Course Code: AC 122
Credit Value: 3 Credits
Contact Hours:
Lectures: 3 hours per week
Tutorials/Practical Sessions: 1 hour per week
Duration: 15 Weeks (One Semester)
Prerequisite: Business Mathematics or Mathematics and Quantitative Reasoning
Primary Tools: Scientific calculator, spreadsheets (Microsoft Excel or equivalent), and statistical tables
1. COURSE DESCRIPTION
Business Statistics introduces students to the statistical methods used in business, accounting, economics, and management decision-making. The course emphasises the collection, organisation, presentation, analysis, and interpretation of data to support informed decision-making under conditions of uncertainty.
Students develop practical statistical skills through the use of real-world business data, with particular emphasis on descriptive statistics, probability theory, probability distributions, sampling techniques, estimation, and hypothesis testing. The course integrates statistical concepts with practical applications relevant to business organisations and the public sector.
2. COURSE OBJECTIVES
By the end of this course, students should be able to:
Explain the role of statistics in business, accounting, and managerial decision-making.
Collect, organise, and present business data effectively.
Apply descriptive statistical techniques to summarise and interpret data.
Use probability concepts to model uncertainty in business situations.
Apply basic inferential statistical methods to business data.
Interpret statistical findings to support managerial and accounting decisions.
3. LEARNING OUTCOMES
Upon successful completion of this course, students will be able to:
Organise and present data using appropriate tables, charts, and graphs.
Calculate and interpret measures of central tendency and dispersion.
Apply the principles of probability to solve business-related problems.
Use probability distributions to model practical business and economic scenarios.
Perform basic statistical inference using sample data, including estimation and hypothesis testing.
Communicate statistical findings clearly and effectively in business and professional contexts.