Introduction Within task one, I will be exploring information in terms of breaking down selective information, analysing the distribution of the data and finding out whether there is a relationship of ii variables. Within task two I will endure out research on the most up to day of the month information regarding clerical and male/female salaries at bottom the joined Kingdom, I will then comp be the data anchor with the data relating to the information in spite of appearance task one. Breakdown by Gender Tally for Discrete Variables: Gender Gender Count Percent f 216 45.57 m 258 54.43 N= 474 As you can see from the pie chart and the tally for discrete variables, the total percentage for males is 54.43% which is 258 male workers and females is 45.57%, which are 216 female workers. From these results we can see that the male population is higher(prenominal) than the female population. In terms of actual workers there is a difference of 42 workers. However although this case I view that overall there is no gender discrimination inside this company as the figures are similar. Breakdown by hire out mob Tally for Discrete Variables: assembly line cat Job cat Count Percent 1-clerical 363 76.58 2-supervisory 27 5.
70 3- managerial 84 17.72 N= 474 The stripe graph shown above presents the number of employees working within each job category, which are clerical, supervisory and managerial positions. From the bar graph we can see that there is a ofttimes higher rate of workers within the clerical job category with a number of 363 employees (76.58%). The supervisory job category has 27 employees (5.70%) and finally the managerial job category has 84 employees (17.72%). thusly this indicates that there is a higher number of people within the clerical industry, there are many reasons why this could be the case. For example the clerical job industry may afford more jobs available then compared to the supervisory and managerial... If you want to seize a full essay, order it on our website:
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