Big Data Project Project Description
Big Data Project
The general description of this project stems from research associated with self-efficacy and its relationship with academic performance and persistent.
The standard project is to use multiple regression analysis to analyze a data set. The data set is a study of student persistent enrolling in the next semester based on Gender, Age, GPA, a 22 questionnaire on self-efficacy, and student enrollment status.
The educational researcher wants to study the relationship between student enrollment status as it relates to gender, age, GPA, and the total response to a 22 questionnaire survey.
The data consist of 132 students at a 2-year college. The data is in pdf format, so it will require input to Excel.
For the qualitative variables use the following to prepare data.
Gender – 0 represents female, 1 represents male
Age – 0 represents student age (18 – 25), 1 represents student age (26 – older)
GPA – student’s current grade point average
Total Q – total of the 22 questions (all question responses come from a scale of 1 – 5, where 5 high.
Enrollment status – 0 represents not enrolled, 1 represents enrolled.
Items to turn in
1. Excel worksheet must include the following
a. data review and update, data does have some wrong inputs so it will require updates, also check for any outliers and remove,
b. column setup,
c. data analysis for regression analysis.
d. include a residual output, may require research
See examples of how to use Multiple Linear Regression using Microsoft Excel.
2. Word document to include the following,
a. The estimated multiple regression analysis equation.
b. Does the model work? Research this question, use the Significance F value and compare it using p-value.
c. How well does the model work? Research this question using p-values and R Square.
d. Which variables contribute to the model? Research this question using p-values.
e. General interpretation of the data and the data analysis.
a. If the dataset was only given in PDF format, attempt to translate the PDF with technology to Excel format. This process must be explained in detail.
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