Quantitative analysis Essay Example | Topics and Well Written Essays - 2250 words

Quantitative summary - Essay ExampleThe standard is based on a proper sequence, and time intervals are equally distant and uniform (Schelter, Winterhalder et al. 319). The main aim of this kind of abridgment is to determine any possible existence of a pattern or sequence in a given set of data. The time series analysis itself offers variety of methods, that is to say the forecasting approach, the univariate approach, which involves limited variables, and other advanced techniques like Gaussian and Box-Jenkins model. Large number of events can be counted as examples of time series analysis that we see in our daily life in our mo activities. For example, the constant rise in the inflation rate, the unemployment rate, the rise in salary, local currency depreciation, annual budgets theme and comparison with the early(prenominal) values and prediction of upcoming budgets all these things are possible through the powerful instrumental role known as time series analysis. Time ser ies analysis is a bulky entity in itself and contains various other methods and approaches, which makes it one of the most effective means of quantitative analysis of data. discordant types of Time Series Analysis Continuous time series As the name applies, the samples and patterns are accumulate over a unremitting and recurrent time frame (Tsay 287). Discrete In contrast to continuous time series, the discrete method attains certain values at fixed and definitive moments. Deterministic vs. stochastic The data so obtained is deterministic in nature, that is, the accuracy and predication level is relatively high and accurate. The stochastic method involves relative use of probability and assumption based on the trends. These trends are collected from the past times and present values, which enables the prediction of future trends. Advantages There are a number of advantages attached to this form of analysis the first and foremost is the possibility to analyze things based on soli d foundations and evidence, which involves study and consideration of samples and patterns from past values and may include the data from present values if a future trend is to be determined. It enables gathering data on a more than consistent pattern that is relatively more reliable. another(prenominal) advantage of this pattern is the co-relational factor and dependency between the variables involved. With the element of dependency in the analysis, the results become more reliable and consistent, and in such cases a change in one, or any other alteration, dexterity result in disturbance and variation in the other, so the entire arrangement is under a uniform control and each entity is dependent on the presence and behavior of the other entity in the system under analysis. Due to this feature, it has the ability to determine the linear and non-linear functions and relations. Other salient features of time series analysis include constant observation, with no data missing in-betw een, and the time slots and observational chunks are equally spaced. Applications though time series analysis finds its application in a large number of places and circumstances, the most notable of them is the process of forecasting. Forecasting is an essential tool of managerial world and in other processes where predictions are needful and made about a certain future value. Time series analysis is the best tool for it. The process is naturally designed in such a way that completely fulfils the requirements of a