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Time-Series Analysis For Marketing in R (Pt. 1)

January 30, 2026February 7, 2024 by Daran J. Johnson

Introduction Time-series analysis is a powerful way to predict events that occur at a future time. One of the most common uses in eCommerce is for sales events. In this post I am going to use the forecast package to explore an ARIMA time-series model in R. I have covered what an ARIMA model is … Read more

Categories Forecasting, R, SQL Tags data exploration, time-series Leave a comment
  • Channel Attribution
  • Data Fundamentals
  • Experimentation
  • Forecasting
  • Hypothesis Testing
  • Marketing Measurement
  • Python
  • R
  • Regression
  • SQL

a/b testing advanced sql for analysts arima armstrong's axioms auto-correlation bigquery boyce-codd normal form closure cohort analysis correlation custom metrics data cleaning data exploration data modeling data studio data tables data visualization etl frequentist functional dependencies ga4 ggplot glmnet google ads googleanalyticsr package heath's axiom join dependencies k-fold cross-validation kendall tau media optimization modeling multi-channel attribution normalization pearson r prediction risanen's theorem rmarkdown shiny spearman rho spreadsheets stationarity time-series unit root white noise window functions

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