regression analysis

Title: Exploring the Correlation Between Pre-Admission Criteria and Academic Performance in Dental Education Background: This project is part of a comprehensive research study aimed at investigating the relationship between various pre-admission criteria and academic performance, specifically Grade Point Average (GPA), among dental students. The study has collected data from a sample of 900 dental students from eight colleges, encompassing both governmental and private institutions. Objective: The primary objective of this regression analysis is to delve deeper into understanding how different pre-admission criteria such as high school grades, achievement test scores, and aptitude test scores, along with various demographic and academic factors, correlate with the academic performance of dental students. This analysis is integral to addressing a gap in existing literature regarding the predictive validity of admission criteria in dental education. Data Overview: Sample Size: 900 students. Independent Variables: High school grades, achievement test scores, aptitude test scores, age, gender, marital status, parents' education level, type of accommodation, year in dental school, type of dental school (government or private), history of suspension from courses, and self-reported English language proficiency. Dependent Variable: Current GPA score. Data Type: Mixed (both continuous and categorical variables). Requested Analysis: Multiple Regression Analysis: To assess the influence of various independent variables on the GPA (continuous outcome variable). Model Building: Development of an appropriate regression model that includes checking for multicollinearity, interaction effects, and potential non-linear relationships. Diagnostics: Validation of model assumptions (linearity, homoscedasticity, normal distribution of residuals). Interpretation of Results: Detailed interpretation of regression coefficients, significance levels (p-values), and the model's explanatory power (R-squared/Adjusted R-squared). Reporting: Provision of a comprehensive report detailing the methodology, findings, and statistical significance, including relevant tables and graphical representations. Software Preference: The analysis should be performed using IBM SPSS, as our preliminary analysis was conducted using this software. However, we are open to other statistical software recommendations if deemed more suitable for our data. Timeline: We are aiming to have the analysis completed within 3 days from the start date, to align with our project timeline for publication. Confidentiality and Data Security: The data shared for this analysis is confidential. The statistician is expected to adhere to strict data security protocols and ensure that all information is handled with the utmost discretion.