The human resource (HR) manager for a large educational establishment is anxious to know why there is a large variation in the take up of extra paid hours in time of need (mostly during weekend).She asks three of her staff to conduct a survey among employees of the establishment by using a questionnaire of "employee engagement" during one week in June 2019.The short questionnaire used for the survey as well as the data collected can be found on an Excel file named "Engagement". There are two worksheet, one for the questionnaire used and the other worksheet for the raw data collected from the employees.The data worksheet has 18 columns. Column A "Employee" is simply a column to identify the customer surveyed.Each of the other 17 columns refer to a question - Column B refers to the gender question, Column C refers to the age question etc.Column F contains data for the variable "Hours". This variable was not one of the questions asked to employees but collated by the HR department for each employee. These refer to the total additional (paid extra) hours carried out by employees mainly during weekends.The HR manager has employed you as data analyst to conduct this investigation. Your analysis should use the statistical facilities on Excel to produce the requirements below.
1. Label the codes for the categories of the following variables:
Length of service
2. Produce frequency and percentage frequency tables for each of the following variables:
Consider now the variable "Hours (£)". Calculate,
Length of service
Draw the graphical representation for each of the following variables:
Department (Pie chart)
Length of service (Bar chart)
Hours (Histogram) using the following categories:
The minimum, maximum, median, quartiles, mean and standard deviation.
• The mean and standard deviation split by attenders (and non-attenders) to training.
5. Produce a cross-table between each of the following two variables and draw an appropriate multiple bar chart:
Training and Gender
Training and Length of service
Draw a scatter diagram and calculate the correlation coefficient between the variable[Hours] and [Job], where the variable [Job] is the total score for the job items and calculated using the following formula:
Do you attend staff training regularly?
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