Describe when to use of a time series forecasting techniques and what assumption are made?

Statistical approaches are used to forecast variables by analysing historical data. Forecasts are generated by analysing historical data trends. This signifies that no prior information is required to predict the variable. The fundamental idea is that previous or historical patterns are effective indicators of upcoming or future developments. On the other hand, Causative techniques illuminate the functional link between variables and, as a result, the independent variables or predictors that impact the variables' behaviour. The basic assumption is that the projected variable will have a cause-and-effect relationship with other variables. The prediction in this scenario is based on a number of factors and probabilities, which is not the case with statistical approaches. Forecasting statistics are a method or procedure for forecasting events using statistics. By analysing past trends, statistical forecasting methodologies provide forecasts regarding longer-term or imminent occurrences. On the other hand, the casual approach predicts events by assuming variables that are likely to affect or change in the future. a some of the fundamental premises