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Statistics - Time Series Prediction.

📊 Time Series | Statistics Explained In this video, we explain Time Series Prediction and Spearman Rank Correlation. You will learn how to model historical data to predict future variables and how to measure the relationship between qualitative data like student grades. 🔹 Topics covered in this video: • Introduction to Time Series Prediction • Converting time (years/months) into mathematical values () • The Brief Method for odd and even numbers of periods • Calculating constants and for the prediction equation • Spearman Rank Correlation for qualitative data 🔹 Key Concepts: • Converting Time Series to values where simplifies calculations • Prediction Equation: • In even-numbered series, the values skip zero (e.g., -3, -1, +1, +3) • Spearman's represents the difference between ranks, where must equal zero 📊 Formulas: • Intercept (): • Slope (): • Spearman Coefficient (): 🔹 Real-world applications: • Predicting future sales based on past trends (e.g., 2019–2024) • Determining the specific year a target value will be reached • Measuring correlation between subjects like Insurance and Statistics • Analyzing monthly profit increases or decreases This video is ideal for students, beginners, and anyone studying business statistics and data analysis. #TimeSeries #Statistics #SpearmanCorrelation #DataAnalysis #Math #Prediction #Correlation #TrendAnalysis