Data preparation: Outliers

In this week’s issue, the final entry in our series of data preparation tutorials, we discuss the influence of outliers on our time series analysis. Dealing with outliers can be tricky, as they might result from a number of factors,…

Data preparation: Concentration of Values

This week, we continue with the fourth issue in our ongoing data preparation series by addressing two important anomalies commonly found in sample data: (1) concentration of values – either a tight range (e.g. proportions) or a wide dispersal over…

Data Preparation: Homogeneity

This week, we unveil the third issue in our ongoing series of tutorials on data preparation. This time, our focus is another bedrock assumption in time series modeling: homogeneity, or the assumption that a time series sample is drawn from…

Data preparation – Missing Values

This issue is the first in a series of articles that explore the data preparation aspect of time series analysis. Data preparation is often overlooked by analysts, but we believe it is a vital phase that wields a vast influence…