ULMS Electronic Module Catalogue |
The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module. |
Title | BUSINESS STATISTICS | ||
Code | ECON154 | ||
Coordinator |
Dr M Chaturvedi Economics Mayuri.Chaturvedi@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2022-23 | Level 4 FHEQ | Second Semester | 15 |
Pre-requisites before taking this module (other modules and/or general educational/academic requirements): |
Modules for which this module is a pre-requisite: |
Programme(s) (including Year of Study) to which this module is available on a required basis: |
Programme(s) (including Year of Study) to which this module is available on an optional basis: |
Teaching Schedule |
Lectures | Seminars | Tutorials | Lab Practicals | Fieldwork Placement | Other | TOTAL | |
Study Hours |
24 |
6 |
6 |
36 | |||
Timetable (if known) |
120 mins X 1 totaling 24
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60 mins X 1 totaling 6
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60 mins X 1 totaling 6
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Private Study | 114 | ||||||
TOTAL HOURS | 150 |
Assessment |
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EXAM | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Assessment 1: Midterm Assessment Type: Written Examination Duration: 1 hour Weighting: 30% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL Penalty Applies Anonymous Asse | 1 | 30 | ||||
Assessment 2: Unseen Examination Assessment Type: Written Examination Duration: 2 hour Weighting: 70% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL Penalty Applies Ano | 2 | 70 | ||||
CONTINUOUS | Duration | Timing (Semester) |
% of final mark |
Resit/resubmission opportunity |
Penalty for late submission |
Notes |
Aims |
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The purpose of the module is to provide an introduction to business statistics for the non-specialist. The course aims to provide a broad understanding of the nature of variability and why it is an issue for managers. It will also provide students with the ability to derive and understand a variety of graphs and statistics which can be produced in Excel and which provide a means for managers to make intelligent use of statistics in the process of management and decision-making. |
Learning Outcomes |
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(LO1) Explain the nature of variability and why it is important for managers |
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(LO2) Describe and analyse data using graphs and summary statistics |
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(LO3) Explain basic principles of sampling and apply them to management contexts |
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(LO4) Model data using standard probability distributions |
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(LO5) Describe and analyse attribute data |
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(LO6) Explain the nature of random sampling error and the need to place a margin of error around estimates |
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(LO7) Calculate a margin of error to place confidence limits on estimates |
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(LO8) Explain and interpret control charts and propose appropriate improvement strategies |
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(LO9) Analyse the relationship between quantitative variables using simple regression and correlation techniques |
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(S1) Numeracy/computational skills - Confidence/competence in measuring and using numbers |
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(S2) Numeracy/computational skills - Problem solving |
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(S3) Numeracy/computational skills - Numerical methods |
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(S4) Numeracy/computational skills - Reason with numbers/mathematical concepts |
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(S5) Critical thinking and problem solving - Critical analysis |
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(S6) Create and manipulate Excel spreadsheets and create tables and graphs in Excel and export them to Word |
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(S7) Use standard data analysis tools in Excel |
Teaching and Learning Strategies |
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Teaching Method: Lecture Teaching Method - Seminar Skills/Other Attributes Mapping Skills / attributes :Use standard data analysis tools in Excel Skills / attributes: Create and manipulate Excel spreadsheets and create tables and graphs in Excel and export them to Word Skills / attributes: Critical thinking and problem solving - Critical analysis Skills / attributes: Numeracy/computational skills - Reason with numbers/mathematical concepts Skills / attributes: Numeracy/computational
skills - Numerical methods Skills / attributes: Numeracy/computational skills - Problem solving Skills / attributes: Numeracy/computational skills - Confidence/competence in measuring and using numbers |
Syllabus |
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Data and Statistics; categorical and quantitative data; measures of location and variation. Control charts and improvement strategies |
Recommended Texts |
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Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module. |