Excel And SPSS E-Portfolio Guidelines
Excel And Spss E Portfolio Guidelinesthe Excel And Spss Portfolio Will
The Excel and SPSS Portfolio will consist of all the Microsoft Excel and SPSS lab assignments. It should be in the same sequence as that of being instructed, generally from lab assignment 1 to 8. The portfolio will consist of a cover page for the entire portfolio and will also consist of a cover page for each lab assignment. The format of the cover page for the entire portfolio and each lab assignment is provided below. The written text will be double-spaced, font size 12, and Times New Roman.
Please set the Top, Bottom, Left, and Right Margins to 1 inch. Each lab assignment should have its own cover page, followed by the explanatory paragraph, and printed output pages. The Excel and SPSS Portfolio must look professional. The Portfolio must consist of a cover page followed by table of contents, followed by all computer laboratory assignments. Sample portfolio are available with peer tutor and instructors, please feel free to stop by and look at the old sample portfolios.
PLEASE NOTE THAT THE PORTFOLIO IS SUBMITTED DIGITALLY AS A SINGLE PDF FILE TO DROP BOX ON D2L. Please note that the explanatory paragraphs, the title page, table of contents, and title page for portfolio will all be written in Word document and converted to PDF. The lab outputs for Excel, where you will create the tables, will be copied and pasted into Word document and converted to PDF. The output from SPSS will be exported to PDF. When everything is ready, combine the separate PDFs into one file using an online PDF joiner and ensure correct sequence. Page numbers for the table of contents are optional if you have Acrobat Professional.
Make sure to submit by the due date and time, as only one single PDF file can be uploaded to D2L. Failure to comply will result in a failing grade.
Paper For Above instruction
The purpose of this portfolio is to compile and demonstrate proficiency in statistical and data analysis using Microsoft Excel and SPSS software. It involves conducting various analyses including frequency distributions, stem-and-leaf plots, regression analyses (enter, stepwise, hierarchical methods), one-way ANOVA, and independent samples T-tests. The assignment emphasizes proper formatting, professional presentation, and comprehensive interpretation of results, which are essential skills for data analysis in academic and applied research settings.
The portfolio must be structured with a cover page, table of contents, and individual lab assignments, each with its own cover page and explanatory paragraph. These submissions must be consolidated into a single PDF document, following strict formatting guidelines such as double spacing, Times New Roman font size 12, and 1-inch margins on all sides. Importantly, students should include visual outputs from SPSS and Excel—either as pasted images or exported PDFs—and ensure consistency in style and formatting throughout the document.
The lab assignments are designed to evaluate multiple competencies. First, students will perform frequency and descriptive analyses to understand variable distributions, commenting on skewness, kurtosis, and normality assumptions. Next, multiple and stepwise regression analyses will test predictive relationships among variables, with clear reporting of statistical coefficients, significance, and multicollinearity diagnostics. Additionally, students will execute ANOVA and T-tests to compare group means across categories like gender, interpreting significance and test assumptions, including homogeneity of variances.
All analyses require detailed interpretation to demonstrate understanding. For example, regression output should include the prediction equation with coefficients, R-squared, adjusted R-squared, F-test significance, and evaluation of predictors' significance. Commentaries should discuss the implications of these findings for theoretical and practical purposes, providing insights into the model's predictive power and limitations.
Visual representations like conceptual models and correlation matrices should accompany the analyses to facilitate comprehension of relationships among variables. These should be meticulously formatted and integrated into the final PDF, with writing adhering to academic standards and clarity.
In sum, this portfolio is a comprehensive demonstration of data analysis skills, including data preparation, analysis execution, result interpretation, and professional report writing—all consolidated into one polished document delivered digitally. Adherence to the guidelines will showcase the student's ability to organize, analyze, and communicate quantitative data effectively for academic or professional purposes.