Investigating the Gender Pay Gap in the UK: A Data Analysis Report

Tasks

The gender pay gap or gender wage gap is the average difference between the remuneration for men and women who are working. Women are generally considered to be paid less than men. UK Gender Pay Gap Regulations came into force in April 2017, requiring organisations with 250 or more employees to publish their gender pay gap data each year. You work as a consultant for Newton Data Solution limited, a data analysis firm and you have been requested by the line manager to conduct a detailed investigation on the problem of gender pay gap in the UK for a local newspaper. Using the government-based data set provided, you will devise a report that provides insight on Gender pay gap in the UK.

You will use the secondary data provided retrieved from ONS for your analysis. Your data will be analysed using appropriate software packages (i.e. SPSS/NVIVO/Tableau/Excel) and be visualised for easier interpretation. You will be required to support your data set with insight  from other selected information sources and to present this in a form appropriate for a specialist and not specialist audience. You have been given 72h to complete this task.

Your report should cover the following points

• A brief review of the literature on the topic
• Review the Data sets and its implications for strategic leadership
• Data Analysis and visualisation of the data set to provide insight using the appropriate statistical packages (i.e. SPSS/NVIVO/Excel/Tableau)
• Evidence of training completed on LinkedIn learning (screenshots of SPSS, Tableau & NVIVO certificates provided in appendix) [15% of overall mark]

On successful completion of this assessment, you will be able to:

• Critically evaluate ethical and methodological considerations associated with applied secondary research, considering the implications for strategic leadership and organisational development.
• Evaluate, and discriminate between, sources of secondary data and information, justifying relevance to the task and context.
• Select, justify and apply appropriate data analysis tools.
• Devise and justify use of ethical, workable and creative solutions in the light of evidence.