/regression-1

A time series project that focuses on store sales forecast for a grocery retailor in Ecuador named Corporation Favorita.

Regression Analysis for Forecasting Store Sales at Corporation Favorita, Ecuador

Introduction

In the dynamic landscape of grocery retail, accurate predictive sales are crucial for success. This project delves into a distinctive sales forecasting for Corporation Favorita in Ecuador, with the goal of securing a competitive edge and nurturing long-term growth.

Project Structure

Project Title and Introduction

  • Title and brief project overview.

Project Planning and Initiation

  • Creation of the working environment and importation of necessary libraries.

Data Collection and Preparation

  • Collection and preparation of datasets from Database, OneDrive, and GitHub.

Exploratory Data Analysis (EDA)

  • Steps including data summary, handling missing values, data visualization, and distribution analysis.

Data Modeling and Analysis

  • Selection, training, and evaluation of different models.

Results and Findings

  • Identification of best-performing models and recommendations.

Technical Content

Data Collection and Processing

  • Collection of historical sales data, handling missing values, and ensuring data consistency.
  • Use of interpolation technique to estimate missing data points, preserving trends and patterns.

Time Series Analysis

  1. Understanding Time Series Data:

    • Analysis of total sales based on different groupings (City, Cluster, State, Store Type).

  2. Visualization Techniques:

    • Box plots, histograms, subplots, and bar plots to identify patterns and trends.

  3. Stationarity:

    • Application of Augmented Dickey-Fuller (ADF) and KPSS tests to assess stationarity.

  4. Model Selection:

    • Exploration of Auto Regressive, Sarima, and Arima models for forecasting.

  5. Forecasting:

    • Implementation of selected forecasting models, evaluation using metrics (MAE, RMSE).

Reporting and Visualization

  • Utilization of Power BI interactive dashboards and reports for effective communication.

Conclusion and Recommendations

  • Statistical analysis reveals a significant impact of external events (e.g., earthquake) on sales.
  • The earthquake led to a temporary disruption, with sustained higher sales levels for a few months.
  • Visual evidence and statistical tests support the conclusion.

References

Project Links