Velocity Wheels

**"Velocity Wheels"**analyzed the truck sales time series data using a comprehensive approach. The first step involved data cleaning and preprocessing to ensure accuracy and consistency. Missing values were addressed, and outliers were carefully examined to prevent any distortions in the analysis.

Next, a thorough exploratory data analysis (EDA) was conducted to gain insights into the underlying patterns and trends. Visualizations, such as line charts and bar graphs, were employed to illustrate the fluctuations in truck sales over time. Seasonal patterns, if present, were identified to understand any recurring trends.

Statistical measures, including mean, median, and standard deviation, were calculated to provide a quantitative understanding of the central tendency and variability in the data. Time series decomposition techniques were applied to break down the data into its trend, seasonal, and residual components, offering a clearer picture of the overall sales dynamics.

Moreover, advanced forecasting models, such as ARIMA or Exponential Smoothing, were employed to predict future truck sales based on historical patterns. The accuracy of these models was evaluated using appropriate metrics, ensuring the reliability of the forecasts.

In conclusion, "Velocity Wheels" utilized a meticulous blend of data preprocessing, exploratory analysis, and advanced forecasting techniques to derive actionable insights and strategic recommendations for optimizing truck sales in the dynamic market landscape.