ARIMA (AutoRegressive Integrated Moving Average) is a popular time series forecasting method that models a time series as a combination of autoregressive (AR) and moving average (MA) components, with the added ability to handle non-stationary time series through differencing. Let’s consider an example of forecasting the monthly sales of a particular product over the past […]

Suppose we want to determine whether there is a difference in the average test scores of students in three different schools: School A, School B, and School C. To test this hypothesis, we randomly select a sample of students from each school and administer a test. The data we collect is as follows: To perform […]

Learning statistics is essential for becoming proficient in data science. Here are some guidelines for learning statistics for data science: In summary, learning statistics for data science requires a solid foundation in basic statistical concepts, practical application of these concepts, and an understanding of statistical models. Seeking help when needed and practicing regularly are also […]