Time Series Analysis

• Forecasting Methods
  • Judgmental Forecasts
  • Bayes Rule
  • Simple Prediction Rules
  • Small Data is Big Data in Disguise
  • Fitting and Forecasting
• Time Series Data
  • Read and Plot Data
  • White Noise
  • Random Walk
  • Seasonal Plot
  • Boxplot of Seasonal and Trend Distribution
  • Smoothen a Time Series
• Forecasting with Regression
• Exponential Smoothing Forecasts
  • Simple Exponential Smoothing
  • Holt’s Model for Trend
  • Winters’ Exponential Smoothing Model
• Stationarity and Forecastability
  • How to Make a Time Series Stationary?
  • Why does a Stationary Series Matter?
  • Test for Stationarity
  • Estimate the Forecastability
  • Granger Causality Test
• Components of Time Series
  • Cyclic vs Seasonal Pattern
  • Decompose a Time Series
  • Detrend a Time Series
  • Deseasonalize a Time Series
  • Test for Seasonality
  • Missing Values in a Time Series
• Autocorrelation and Partial Autocorrelation Functions
  • Autocorrelation
  • Partial Autocorrelation
  • Plot Lags
• ARIMA Models
  • Identify the Order of Differencing
  • Identify the Order of the MA and AR Terms
  • Identify the Optimal ARIMA Model
  • ARIMA Forecast
  • ARIMA vs Exponential Smoothing Models
• Seasonal ARIMA (SARIMA) Models
  • Build SARIMA Model
  • SARIMA Forecast
  • SARIMAX Model with Exogenous Variable
• Case Study