Assignment Task
Task
Purpose: Prepare a report for your client to allow them to gain insights into the demographic characteristics of their employees and possible links to absenteeism from work.
2500 words maximum, excluding illustrations (tables, charts, graphs) and appendices Business Analytics Applications: descriptive analytics, cluster analysis
Background: The Absenteeism dataset in SAS contains data on employees’ absenteeism and demographic characteristics. The client is interested in whether there are certain demographic characteristics of employees that makes them more susceptible to workplace absence.
Guidelines: Use only demographic data for the cluster analysis (age, body mass index, distance to work, education, height, pets, service time, social drinker, social smoker, sons, transportation expense, weight). Note that you may need to convert some of the measures such as education, social drinker/smoker to categories. Then start with variable selection and think about the rationale for your chosen variables. You will need to conduct descriptive analytics of your chosen variables (central tendency, variation, shape, correlations etc and identification of missing data). Develop a range of cluster analyses, starting with the numerical data only and default settings and experiment with differing numbers of clusters and variables (including the categorical variables). As a final step, analyse the relationship between your clusters and average “absenteeism time in hours”. DO NOT include absenteeism in the cluster analysis itself (see recordings on Moodle how to do this step). There is no one “right’ answer, so think about and discuss in your report the rationale for the steps you take in the analysis and the reasoning for your preferred cluster model(s).
Format: Business report for client
Executive summary – one paragraph overview of full project including summary of results – 10 marks
Introduction – set the scene and background of issue/problem (broad to specific issues) – 10 marks
Methodology – discuss the rationale and planned steps for your analytics process (ie. details of descriptive analytics and cluster analysis you plan to do – do not include any results in this section) – 20 marks
Body and analysis – descriptive analytics results, quick summary of the process and steps ultimately taken in your cluster analysis present to arrive at your chosen models (between 1 and 3 max), then focus on discussion and interpret of the chosen model(s), examine possible link with absenteeism, and any recommendations (Model = combination of k and set of variables) – 50 marks
Conclusions – wrap up the exercise with recommendations for client – 10 marks
Absenteeism data dictionary
Data Dictionary
Individual identification (ID)
Reason for absence (ICD). Absences attested by the International Code of Diseases (ICD) stratified into 21 categories (I to XXI) as follows:
I Certain infectious and parasitic diseases II Neoplasms III Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism IV Endocrine, nutritional and metabolic diseases V Mental and behavioural disorders VI Diseases of the nervous system VII Diseases of the eye and adnexa VIII Diseases of the ear and mastoid process IX Diseases of the circulatory system X Diseases of the respiratory system XI Diseases of the digestive system XII Diseases of the skin and subcutaneous tissue XIII Diseases of the musculoskeletal system and connective tissue XIV Diseases of the genitourinary system XV Pregnancy, childbirth and the puerperium XVI Certain conditions originating in the perinatal period XVII Congenital malformations, deformations and chromosomal abnormalities XVIII Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified XIX Injury, poisoning and certain other consequences of external causes XX External causes of morbidity and mortality XXI Factors influencing health status and contact with health services.
And 7 categories without (CID) patient follow-up (22), medical consultation (23), blood donation (24), laboratory examination (25), unjustified absence (26), physiotherapy (27), dental consultation (28).
Month of absence
Day of the week (Monday (2), Tuesday (3), Wednesday (4), Thursday (5), Friday (6))
Seasons (summer (1), autumn (2), winter (3), spring (4))
Transportation expense
Distance from Residence to Work (kilometers)
Service time
Age
Work load Average/day
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