Articles
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Monte Carlo Simulations to Explore Uncertainty with Powerful Random Walks
Have you ever wanted to predict the future? While crystal balls and fortune tellers might offer intriguing (yet unreliable) solutions, science and engineering rely on a more robust approach: Monte Carlo simulations. These simulations leverage the power of randomness to tackle problems fraught with uncertainty, helping us make informed decisions in diverse fields ranging from…
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How to Simulate Roulette with Monte Carlo in Python
Ready to take a spin on probability with Python? Let’s build a Monte Carlo simulation for a roulette wheel and visualize the possible outcomes as random walks. Buckle up! 1. Define the Model: A roulette wheel has 37 slots (European version): 18 red, 18 black, and 1 green (0). Your goal is to simulate placing…
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Navigating Market Maze Magic with The Efficient Market Hypothesis
Imagine a stock market where prices instantly reflect all available information, making it impossible to consistently “beat the market.” This is the core proposition of the Efficient Market Hypothesis (EMH), a fascinating and controversial theory in finance. Today, we’ll delve into its core ideas, explore its implications, and examine the ongoing debate surrounding its validity….
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Rock, Paper, Scissors: The Amazing Anomaly of Non-Transitive Data
Our understanding of the world relies heavily on relationships between things. We say a mountain is taller than a hill, a parent loves their child, and one concept leads to another. These connections, often expressed through verbs like “less than,” “loves,” and “leads to,” are transitive in nature. This means if A is connected to…
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Tutorial: Creating a Linear Regression in Python
This tutorial guides you through building a linear regression model in Python, covering importing libraries, loading data, fitting the model, and interpreting results. 1. Import Libraries 2. Load Data Replace with your actual data source: sepal length (cm) sepal width (cm) petal length (cm) petal width (cm) predicted_y species 0 5.1 3.5 1.4 0.2 3.503062…
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How to Use One-Way ANOVA in Python with the Iris Dataset
This tutorial demonstrates how to perform a one-way ANOVA in Python using the sklearn.feature_selection.f_classif function from the scikit-learn library. We’ll work with the iris dataset included in scikit-learn for an example. Importing Libraries: Loading the Iris Dataset: One-Way ANOVA with scikit-learn: Explanation: Interpreting Results: In this example, the f_statistic and p_value will depend on the…
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Hello, World! Welcome to onstatistics.com!
We’re thrilled to officially launch onstatistics.com, your one-stop shop for all things data and statistics! We know navigating the complex world of data can be overwhelming, but fear not! We’re here to guide you through the numbers, simplify concepts, and unlock the power of statistics for everyone. Whether you’re a data enthusiast, a student tackling…
