Final Paper

Introduction

In this final paper, the analysis will be based on a dataset named Education.sav. This file contains a dataset that consists of 9 variables, and 1419 cases (not all of them are valid cases). The variables contained by this dataset are:

• age: This corresponds to the age of respondent
• degree: Respondent's highest degree (The categories are: 0 = Less than HS, 1 = High School, 2 = Junior College, 3 = Bachelor, 4 = Graduate)
• educ: Highest year of school completed
• sex: Respondent's sex (1 = Male, 2 = Female)
• maeduc: Highest year school completed by mother
• paeduc: Highest year school completed by father
• marital: Marital status (1 = Married, 2 = Widowed, 3 = Divorced, 4 = Separated, 5 = Never married)
• husbeduc: Husband's education in years
• Wifeduc: wife's education in years

From the above variables, Age , Educ , Maeduc, Paeduc, Husbedcu anf Wifeduct are scale (ratio) variables. The variables Degree , Sex , and Marital are categorical variables ( Degree is ordinal, and Sex and Marital are nominal).

The level of measurement of the variables involved will determine the type of analysis that can be performed. In this case, there is a mix of categorical and scale variables that provide abundant opportunities for finding appropriate research hypotheses, and the variety of techniques that can be used is fairly varied as well. For example, with these data we could perform different types of parametric tests, such as t-test for independent samples (a ratio variable must be chosen, and one categorical variable should be used to divide the sample into two groups), or ANOVA (similar as above, one ratio variable must be chosen, and a categorical variable will be used to divide the sample into 3 or more categories). For this paper though, the scope of the analyses performed will restricted to the set of four research questions, which are:

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Solution: The downloadable solution consists of 28 pages, 3676 words and 24 charts.
Deliverable: Word Document