Assignment 1: Descriptive Statistics and Central Tendency

• Calculated mean, median, and mode for bike prices and exam scores.
• Explained impacts of outliers on mean and median values.
• Described histogram shapes related to skewness and central tendency.
• Computed frequency distributions and mode for categorical variables.
• Differentiated between sample statistics and population parameters with examples.
• Visualized data distributions with histograms, boxplots, and bar charts.

Assignment 2: Probability and Venn Diagrams

• Solved conditional probability problems (marbles, medical tests) using formulas and Bayes' theorem.
• Calculated posterior probabilities adjusting for test results.
• Analyzed set relationships using Venn diagrams.
• Computed probabilities of mutually exclusive and overlapping events.
• Provided step-by-step mathematical solutions with formula explanations.

Assignment 3: Exploratory Data Analysis (EDA) using Python

• Loaded and inspected the "tips" dataset using pandas.
• Cleaned data by checking for missing values and duplicates.
• Detected and treated outliers using Interquartile Range (IQR) method.
• Performed univariate analysis with mean, median, trimmed mean, range, variance, and standard deviation calculations for numerical columns.
• Conducted frequency counts and mode identification for categorical columns.
• Visualized distributions using histograms, KDE plots, boxplots, and bar charts.
• Explored bivariate relationships through scatter plots and grouped boxplots.
• Created correlation matrix heatmap focusing on numerical variables.
• Summarized insights and findings from the analysis.

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This repository contains solutions demonstrating core skills in statistics, probability, and data analysis relevant to AI and Data Science applications.