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STATISTICS *Root mean squared error Definition: It refers to the square root of mean square error where mean square error is a statistical measure of the second moment of error about the actual value.Example: Target a point with an assumed bulls-eye at the centre. the average squared distance from the centre and the arrow shot on the bulls-eye point represents means square error which its square root in turn gives the root mean square error.*Seasonal effectDefinition: This is a scientific, statistical and calendar related effect which is obtained from the difference between the centered moving averages and the corresponding raw data.Example: The sharp increase in most of the products sales series which is experienced around festive seasons like Christmas in December. *Seasonal model Definition: This is an arithmetic representation of seasonal components which have effects that are reasonably stable in regard to time, magnitude and direction in systematic influence derived from the calendarExample: uncommon climate pattern like snow appearing during summer can be said to be irregular in the model. *Secular trend Definition: This is a statistical phenomenon that does not follow a regular cyclic pattern or seasons but its occurrence spread over a relatively longer time period.Example: production and sales of motor vehicles exhibits a decreasing trend or increasing trend over some long period of time.*Simple composite index numberDefinition: This is a number which can be used in a group of relative variables to compute average relative changes with respect to a given base value. Example: Use of price index to measure relative variations in commodity prices between two periods and the prices are either wholesale or retail. *Simple index numberDefinition: This is a statistical measurement tool for relative changes using a single variable with regard to a given base value.Example: If price index stands at 50 in 2010 compared to 25 in 2001-2002 (the base year) it suggests a price rise of 100% in respect to the base year. *Time series Definition: It is a set of statistic which is gathered at regular time intervals.Example: Recorded semi-annual data for the deaths from road accidents. *Time series residualsDefinition: It arises from fluctuation in the short term in a series which is neither predictable nor systematic. In the case of series with much irregularity, such fluctuations can dominate movements which in turn cover the seasonality and trend.Example: The common moving holiday phenomenon where people know holidays will take place but there is always shifting of exact times like the case of Chinese new year holiday which coincide with Easter. *Weighted composite price indexDefinition: A weighted indices combined in a standardized format which provides important statistical measure of a given occurrence of event over time.Example: The New York composite index is capital market with weighted groupings estimated at 4500 stocks which is listed on the NYSE.ReferenceVogt, W. P., amp. Johnson, B. (2011). Dictionary of statistics amp. methodology: A nontechnical guide for the social sciences. Thousand Oaks, Calif: Sage.