Statistical Modelling - Assignment PDF
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Added on 2021-06-17
Statistical Modelling - Assignment PDF
Added on 2021-06-17
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Running Head: STATISTICAL MODELLING ASSIGNMENTStatistical Modelling AssignmentName of the StudentName of the UniversityAuthor Note
STATISTICAL MODELLING ASSIGNMENT1Table of ContentsSection 1: Introduction................................................................................................................................2Section 2: Descriptive Statistics...................................................................................................................2Section 3: Inferential Statistics....................................................................................................................4Section 4: Discussion and Conclusion..........................................................................................................6References...................................................................................................................................................8
STATISTICAL MODELLING ASSIGNMENT2Section 1: IntroductionIn Australia, there are differences in the salaries of men and women. This difference in salary isknown as gender gap or gender inequality. There are various reasons for this gender discrimination. Oneof the major reasons id that there are discriminations at the time of hiring. Other than that, the salarystructure of the industries in which women are working might be different from the salary structure inwhich women are working (Australia 2014). A lot of other reasons are also existent. This study is aimedmostly towards assessing the different aspects affecting the occupation and salary for different gender. The most important thing that is necessary for conducting this research is data which has beencollected from the website of Australian Taxation Office (ATO). The dataset considered is a subset of theoriginal dataset available in ATO website. Data on 1000 Australian people have been sampled to formthe subset for the study. Information about variables such as gender, occupation of the respondents,the salary of the respondents, deductions from salary for gifts and donations are stored in the datasetretrieved from the ATO website. As the data is collected from the ATO website, and not collecteddirectly from the field of survey for the purpose of the analysis, this data is known as secondary data.The variables gender and occupation are categorical variables and the variables salary and deductionsare numeric variables. Table 1: First Five Cases of the DatasetFor the second part of the analysis, a survey has been conducted. A sample of 60 participantswere selected randomly for the survey. The gender and the salary of the respondents were recordedfrom the survey. In this case, the data has been collected directly from the respondents via a survey withrelation to the research interest. Thus, this data is known as Primary data. People in general are alwaysuncomfortable in sharing information such as income. Thus, there have been a lot of responses wherethe income is unavailable or the respondents are unemployed resulting in no monthly income. Section 2: Descriptive StatisticsFor the variable occupation code, the occupation of people has been recoded to differentnumbers. “0” indicates that the occupation is not specified or listed, “1” indicates Managers, “2”indicates Professionals, “3” indicates Technicians and Trades Workers, “4” indicates Community andPersonal Service Workers, “5” indicates Clerical and Administrative Workers, “6” indicates SalesWorkers, “7” indicates Machinery operators and Drivers, “8” indicates Labourers and “9” indicatesConsultants, apprentices and type not specified or listed. To summarize the variable occupation andestablish the relationship between the variable occupation and gender, it can be seen from the multiplebar graph given in figure 2.1 that most of the female workers are either clerical or administrativeworkers or their occupation is not listed. In occupations like Professionals, community and personalservice, clerical and administrative posts and also in sales, women are more probable to work than men.In all the other types of occupation, men are more probable to work than women.
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