brianotiodhiambo-source/analystlab-week3-statistics-probability

Week 3 Statistics and Probability Assignment completed during the AnalystLab Africa Data Science Internship Program using Titanic and Housing datasets. # AnalystLab Africa Data Science Internship ## Week 3: Statistics & Probability ### Intern Brian Odhiambo ### Overview This project was completed as part of the AnalystLab Africa Data Science Internship Program (Week 3). The objective was to apply statistical analysis techniques to two real-world datasets and derive meaningful insights through descriptive statistics, probability distributions, hypothesis testing, and correlation analysis. ### Datasets Used #### 1. Titanic Dataset Objective: Analyze passenger information and identify factors that influenced survival. #### 2. Housing Price Dataset Objective: Analyze housing characteristics and determine factors that influence house prices. ### Tasks Completed - Data Loading - Descriptive Statistics - Probability Distributions - Hypothesis Testing - Correlation Analysis - Statistical Interpretation - Insights and Conclusions ### Tools & Libraries - Python - Pandas - NumPy - Matplotlib - SciPy - Jupyter Notebook ### Key Findings #### Titanic Dataset - Average passenger age was approximately 29 years. - Passenger class had a significant relationship with survival. - Higher ticket fares were associated with higher survival rates. - Age showed a weak correlation with survival. #### Housing Dataset - House area had the strongest positive correlation with price. - Bathrooms and stories positively influenced house prices. - Housing prices showed substantial variation across properties. ### Repository Contents - Week3_Statistics_Probability.ipynb - Week3_Summary_Report.pdf (or .docx) - cleaned_titanic.csv - cleaned_housing.csv - README.md ### Internship Program AnalystLab Africa Data Science Internship Program Week 3: Statistics & Probability