- Lecturer: Deborah Diana Agaba
- Lecturer: Maureen Mukodha
- Lecturer: Wilber Nuwamanya
- Lecturer: Prof. Mugisha Xavier
- Lecturer: Mpagi Julius
- Lecturer: Warren Tibesigwa
- Lecturer: EPAPHRAS Niwamanya
- Lecturer: Prof. Mugisha Xavier
Below are provisional results for year 3 for Academic Year 2019 / 2020 Semester 1
Below are final results for Bachelor of Business Statistics year 3 for Academic Year 2018 / 2019 Semester 2
- Lecturer: Mpagi Julius
- Lecturer: Warren Tibesigwa
- Examiner: Florence Nakajubi
- Lecturer: Gerald Kaliisa
- Lecturer: Tracy Nimurungi
- Lecturer: Ainembabazi Pamella
- Lecturer: Julian Amanya
- Lecturer: Dr. Samuel Mayanja
- Lecturer: Amina Nankabirwa
- Lecturer: Athanasius Buyondo
- Lecturer: Donatus Rulangaranga Mugisha
- Lecturer: Wilber Nuwamanya
- Lecturer: Prof. Mugisha Xavier
- Lecturer: Mpagi Julius
- Lecturer: Onesmus Kamacooko
- Lecturer: Amina Musuya
- Lecturer: EPAPHRAS Niwamanya
- Lecturer: Migisha Grace Adella
- Lecturer: Charles Obuk
Good morning students. The attached take-home assignment is the first coursework. Please ensure that you follow instructions detailed as per the question paper. Schedule and sequence activities well so as to meet the deadline with quality deliverables.
MAKERERE UNIVERSITY
MAKERERE UNIVERSITY BUSINESS SCHOOL
PRODUCTION STATISTICS TAKEHOME (COURSEWORK ONE) FOR BACHELOR OF BUSINESS STATISTICS OF MAKERERE UNIVERSITY,
ACADEMIC YEAR 2023/2024
YEAR OF STUDY: III SEMESTER: II
COURSE NAME: PRODUCTION STATISTICS COURSE CODE: BBM3204
START DATE: FEBRUARY 18, 2024 TIME: 9:00 AM
END DATE: FEBRUARY 29, 2024 TIME: 9:00 AM
INSTRUCTIONS:
This take-home assignment should be individually done. Attempt all the questions. Use either SPSS, STATA or Excel to analyze production data. You will be required to present and disseminate knowledge in class. Please submit the typed work of not more than 10 pages. Academic dishonesty will automatically lead to disqualification.
Question One
From global and local context, production metrics measure, compare the performance of processes and provide useful data to manage production activities over time. Such production metrics include; costs, quality, volume, downtime, overall operations effectiveness, rate of return, productivity in revenue per employee, asset turnover, inventory turns, return on assets, yield, capacity utilization among others. Accordingly, modelling efficiency and effectiveness of production processes have attracted attention to policy makers, researchers and other stakeholders. As a student equipped with competencies of production statistics, identify organization (s) of your choice to answer the questions that follow;
i) Using the knowledge of production statistics, develop a short story or case of the identified production related issues based on the organization (s) of your choice highlighting context, actions and results with catastrophic evidence. (5 marks)
ii) Gather production data (either secondary or primary data) based on identified production metrics from the organization (s) of your choice and state any two objectives to address the stated production related issues identified in (i) above. (5 marks)
iii) Use the appropriate production statistical tools to develop a production-oriented model (s) basing on the stated objectives and the gathered data in (ii) above. (15 marks)
iv) Suggest the possible evidence-based and action-oriented recommendations to managers and policy makers of the identified organization (s). (5 marks)
END OF EXAMINATION PAPER
Best wishes.
- Examiner: Mr. Lukyamuzi Vicent
- Lecturer: Dr. Gideon Nkurunziza
- Examiner: Douglas Ssenoga
- Lecturer: Ronald Opakrwoth
- Lecturer: Mahadih Kyambade
- Lecturer: Mrs. Tushabe Monica