Psych664 Wk 6 Summative Assessment Research Analysis Report

Understanding how to conduct statistical analysis is essential for research. A foundational understanding of traditional statistical testing and analysis is critical; however, as data becomes more complex, AI can enhance analysis process. In this assessment, you will integrate research and statistics concepts to conduct statistical tests in traditional methods and with AI. Assessment Preparation To complete the assessment, you must first conduct statistical tests. The resources below will help you conduct each required test: • Statistical Testing Guide: Download and read the instructions for conducting statistical tests (descriptive statistics, hypothesis testing, correlational testing) and using AI to analyze statistical data. • Demonstration Videos: Watch the following videos to understand how to conduct each required statistical testing using the Microsoft Excel Analysis ToolPak: • “Descriptive Analysis Guide” • “Inferential t-test Analysis Guide” • “ANOVA Analysis Guide” • “Correlational Analysis Guide” • Happiness and Engagement Dataset: Use this dataset to conduct each required statistical test. Read the following scenario to use for this assessment: You are a research assistant in the psychology department at a growing university. As part of the university’s strategic initiative to enhance employee well-being and retention, the administration asked your department to conduct a study on job satisfaction among university staff. Your specific research focus was on workplace happiness and employee engagement. To conduct the research, you designed and distributed a survey targeting university employees, designed to address the following research questions: • Research Question 1: What variables positively affect workplace happiness and engagement? • Research Question 2: What variables negatively impact workplace happiness and engagement? Your survey collected data from 50 participants and included the following variables: • Demographic information: Gender and age • Workplace dynamics: Quality of relationship with direct supervisors and coworkers • Work arrangements: Telecommuting schedule (e.g., fully remote, hybrid, or on-site) • Outcome measures: Self-reported ratings of workplace happiness and workplace engagement You organized the data into 2 categories for analysis: • Dependent Variables: These are the outcomes you are measuring. In the Employee Happiness and Engagement dataset, the dependent variables are workplace happiness and engagement. • Independent Variables: These are the predictors or factors you are analyzing to determine their influence on employee happiness and engagement. In the Employee Happiness and Engagement dataset, the independent variables include: • Gender • Age • Quality of relationship with direct supervisors • Quality of relationship with coworkers • Telecommuting status (e.g., fully remote, hybrid, or on-site) Your next step is to conduct statistical tests and analyze the data collected using both traditional statistical testing methods and AI-assisted data analysis. Your results will help the university identify key factors that contribute to or detract from a positive work experience, providing valuable insights for university leadership to inform future policies and practices.