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 | STATISTICAL FOUNDATIONS OF BUSINESS ANALYTICS | ||
Code | ECON154 | ||
Coordinator |
Dr M Chaturvedi Economics Mayuri.Chaturvedi@liverpool.ac.uk |
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Year | CATS Level | Semester | CATS Value |
Session 2024-25 | 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) | |||||||
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 2: Unseen Examination Assessment Type: Written Examination Duration: 2 hours 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 |
Assessment 1: Group coursework assignment Assessment Type: Group project Length: 1000 words plus supporting excel files Weighting: 30% Reassessment Opportunity: Yes Penalty for Late Submission: S | 0 | 30 |
Aims |
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The aim of the module is to give students of business administration a conceptual introduction to the field of business analytics, its many applications, and the role statistics plays in it. The module is designed to prepare students for the study of more advanced analytical materials in the future. |
Learning Outcomes |
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(LO1) Students will be able to analyse and interpret data, including variability, attribute etc., using graphs and summary statistics |
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(LO2) Students will be able to explain basic principles of sampling, including sampling error, and apply them to management contexts |
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(LO3) Students will be able to model data using standard probability distributions |
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(LO4) Students will be able to calculate and interpret a margin of error to place confidence limits on estimates |
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(LO5) Students will be able to analyse the relationship between quantitative variables using simple regression and correlation techniques |
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(LO6) Students will be able to calculate and interpret hypothesis tests for differences in means and proportions of sample data |
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(LO7) Students will be able to perform basic statistical functions in excel spreadsheets using standard commands and analysis tool |
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(S1) Team player |
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(S2) Numerate |
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(S3) Excellent written and verbal communicator |
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(S4) Problem solver |
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(S5) IT literate |
Teaching and Learning Strategies |
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Teaching Method: Lecture Teaching Method - Seminar Skills/Other Attributes Mapping Skills / attributes: A problem solver Skills / attributes: Numerate Skills / attributes: A team player Skills / attributes: An excellent verbal and written communicator Skills / attributes: IT literate |
Syllabus |
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This module will cover: |
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. |