Scenario: You are an aspiring data analyst curious about the effects of caffeine on productivity. You hypothesize that individuals who consume caffeine in the morning are more productive throughout the day than those who don't. Data Collection: (HINT: You can absolutely use one of the free tools we covered.) 1. Survey Creation: Design a short survey with questions related to: Caffeine consumption (e.g., "Did you consume caffeine this morning? Yes/No") Productivity measures (e.g., "On a scale of 1-10, how productive do you feel today?") 2. Data Gathering: Over the course of a week, distribute the survey among: Friends or family members. Classmates or colleagues. Online platforms or social media (ensure anonymity and data privacy). 3. Data Recording: Create a simple dataset structure to record responses: Tasks: 1. Data Exploration: Load the collected data and conduct a preliminary analysis. Calculate the mean and standard deviation of the productivity scores for both groups (caffeine consumers vs. non-consumers). 2. Formulate Hypotheses: Null Hypothesis (H0): Caffeine consumption in the morning has no effect on productivity. Alternative Hypothesis (H1): Caffeine consumption in the morning increases productivity. 3. Conduct Hypothesis Test: Choose an appropriate statistical test (e.g., independent t-test). Decide on a significance level (e.g.,