Multivariate Stats Exam Responses
This course covers simultaneous, sequential, and hierarchical multiple regression and other advanced statistical topics. Transforming non-linear data and detecting multicollinearity are discussed. Students analyze data using statistical software and interpret results.
The links below contain a work sample demonstrating my knowledge and abilities in advanced statistical analysis, including a copy of the final exam questions as well as a sample of my statistical analysis on a homework assignment. The purpose of this assignment was to assess my understanding and application of advanced statistical concepts.
This demonstrates the following key competencies:
• Knowledge of various statistical procedures, such as Multiple and Logistic Regression, MGLM / MANOVA, Discriminant and Cluster Analysis, Exploratory and Confirmatory Factor Analysis,
Path Analysis, and Structural Equation Analysis
• Knowledge of APA format and how to report statistical results
• Ability to design experimental, quasi-experimental, and observational studies
• Ability to organize and summarize data
• Ability to use SPSS and AMOS to complete statistical analysis, including interpretation and
communication of results
• Ability to critically evaluate quantitative information
• Ability to evaluate data and determine the best approach to analysis
Univariate Stats Exam Responses
This course covers special correlational methods, elementary experimental design, and hypothesis testing in psychological research.
The links below contain a work sample demonstrating my knowledge and abilities in basic statistical analysis, including a copy of the final exam questions as well as a sample of my responses. The purposes of these assignments were to assess my understanding and application of basic statistical concepts while using SPSS and Excel.
This demonstrates the following key competencies:
• Knowledge of various statistical procedures available and when to use them
• Knowledge of APA format and how to report statistical results
• Ability to design experimental, quasi-experimental, and observational studies
• Ability to organize and summarize data
• Ability to use SPSS and Excel to complete statistical analysis, including interpretation and
communication of results
• Ability to critically evaluate quantitative information