Missing data is one of the most common problems in almost all statistical analyses. If the data is not available for all the observations of variables in the model, then it is a case of ‘missing data’.
estimation in supervised learning, Supervised learning, trend analysisNeural network, popularly known as Artificial Neural Network (ANN) is an information processing system with a large number of nodes and connections as part of a structure which helps in processing complex information.
regressions in supervised learning, Supervised learning, trend analysisOutliers are those data points which are distant from the other observations in the data set. They can be either because of the variability in the data set or due to measurement errors.
detection in supervised learning, Supervised learning, trend analysisThe purpose of this article is to explain the process of determining and creating stationarity in time series analysis. Creating a visual plot of data is the first step in time series analysis. Graphical representation of data helps understand it better.
assumption tests in STATA, empirical analysis with econometrics, STATA for data analysis, stationarity test, time series analysis, trend analysisMonte Carlo simulation is an extension of statistical analysis where simulated data is produced. This method uses repeated sampling techniques to generate simulated data.
estimation in supervised learning, Supervised learning, trend analysis