Avacados Price and pattern analys project

Terms In the project:

  1. Markov Chains Model
  2. Time series Model
  3. Explanatory Model

Markov Chains Model

This is the stochastic model that uses probability distribution from the previous events to predict future outcome. The model is a Mathematics model that outline the probability associated with sequence of events based on the state in previous event.This Model is used when the data is sequential data.

Time seriels Model

This is the Model that uses past data to predict the future outcome.To predict accurately you need to check for three things.

  1. Autocorrelation
  2. seasonality
  3. stationarity

Autocorrelation helps to determine the relationship between the current values and the past values entity. By checking past and current data we can figure out the patterns and predict the future.

Seasonality When an entity shows similar values periodically over a fixed interval ,it makes a way for measuring seasonality.Seasonality makes a way for prediction of day, month ,year and occasion.

Stationality and trend when a statistical time series remain constant over a period of time it’s stationary. In other words the mean and the variances are the same.Staionarity is done by conducting a KPSS Test ,Dickey fuller . This tests evaluate the null hypothesis in one way or another.

Modelling of time series

There are several ways of modeling time series data. The three main ones are moving average, exponential smoothing and arima.

Explanatory Model

This model add variables to the model and also does add other variables to make accurate predictions.

Types of avocado:

In this data we will analysis two types of avocado which are:

  1. Organic
  2. conventional