Location
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Project Overview
I developed this system to analyze temperature data using Mean, Median, and Mode statistical methods, combined with custom prediction algorithms forecasting future temperatures.
Mean
Average temperature level
Median
Typical temperature value
Mode
Most common temperature
Historical Temperature Data
Last 7 DaysLoading historical data...
Statistical Analysis
Mean (Average)
--°C
Average of all temperature values
Median
--°C
Middle value when sorted
Mode
--°C
Most frequently occurring value
Std Deviation
--°C
Spread of temperature values
Temperature Trend & Predictions
7-Day ForecastLoading forecast data...
Trend Analysis
Temperature Predictions
I developed custom prediction algorithms combining Linear Regression, Moving Average, Seasonal Decomposition, and Ensemble methods to forecast future temperatures.
Linear Regression
Statistical trend line
--°C
Moving Average
Smoothed trend forecast
--°C
Ensemble Method
Combined approach
--°C
Conclusions & Evaluation
Statistical Summary
I used mean, median, and mode to summarize temperature data from multiple perspectives, providing comprehensive insights into temperature patterns.
Trend Observations
The analysis reveals clear seasonal patterns with temperature increases toward summer and decreases toward winter, demonstrating predictable cyclical behavior.
Prediction Limitations
My predictions are based on statistical trend analysis. Real weather forecasting requires complex meteorological models considering atmospheric pressure, humidity, wind patterns, and other factors.
Technical Implementation
I built this project with Node.js/Express backend, WeatherAPI integration, and custom JavaScript algorithms implementing linear regression, moving averages, and ensemble methods.