In this piece of coursework, I will be looking at the similarities and differences between jobs and pay that effect the young and old, and between men and women. I will also be looking at other aspects which could affect people’s Work and Pay, or might be caused by it. To do this, I will be looking at both Primary and Secondary information, separately and together, to make as complete a comparison between them as I possibly can.

I obtained the information for my Secondary data from within “Fact File 1998”, which gave me the opportunity to choose several different types of data for comparison. This is a publication produced every year by the Government. It provides statistical data on a wide range of categories, including jobs and pay, by gender and age. It also includes data on car and house ownership, holidays and a wide range of other information which was outside the scope of my coursework investigation.

I obtained my Primary data from members of the public, who were using “The Galleries” shopping arcade in Wigan. I collected the data by means of a sample questionnaire, which was carried out on the afternoon of Wednesday 29th September 1999. I will present my Secondary Data by means of line graphs, bar charts, pie charts, box and whisker diagrams and scatter diagrams. I will obtain Spearman’s Correlation Coefficients and Mean and Standard Deviations. My Primary Data will be represented using the same methods, together with data tables of my questionnaire results.

After completing the individual sections on the Secondary and Primary Data, I will include a section where I will compare my findings, to see if there are any connections between the results I obtained in the Primary Data, and the results I found from data published by the government. Secondary Data Aims My aims in this project, are to explore the relationship between the average gross weekly earnings for full time adult employees, by comparing them on gender and occupation basis.

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I will compare nine different occupational groups, and base my investigation on statistics prepared for April 1997, for Great Britain as a whole. Method I will compare managerial, professional, clerical, service, sales, factory, and other occupations. I will compare male workers of all ages, with female workers of all ages. Hypotheses I will use data for full time employees only, because that is the data provide by the table. I will only use data for employees on full adult rates. I will not break down the data for different age groups, or consider other countries.

I will use data provided from “Labour Market Trends” for August 1997. Prediction I predict that for all occupational groups, men will earn more than women. I also predict that women will generally earn only about two – thirds of the amount that men do, apart from in Secretarial occupations, where the gap should be much closer. Data I chose this set of data to work with, from “Fact File 1998”. I chose to use this data, because it allowed me to use several different Statistical formats, to present my results. This is the table of data I used to find.


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