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Forecasting: Multivariate Regression Exercises (Part-4)

May 1, 2017
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Forecasting: Multivariate Regression Exercises (Part-4)

In the previous exercises of this series, forecasts were based only on an analysis of the forecast variable. Another approach to forecasting is to use external variables, which serve as predictors. This set of exercises focuses on forecasting with the standard multivariate linear regression. Running regressions may appear straightforward but this method of forecasting is Related exercise sets:

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Forecasting: Exponential Smoothing Exercises (Part-3)

April 17, 2017
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Forecasting: Exponential Smoothing Exercises (Part-3)

Exponential smoothing is a method of finding patterns in time series, which can be used to make forecasts. In its simple form, exponential smoothing is a weighted moving average: each smoothed value is a weighted average of all past time series values (with weights decreasing exponentially from the most recent to the oldest values). In Related exercise sets:

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Forecasting: Linear Trend and ARIMA Models Exercises (Part-2)

April 15, 2017
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Forecasting: Linear Trend and ARIMA Models Exercises (Part-2)

There are two main approaches to time series forecasting. One of them is to find persistent patterns in a time series itself, and extrapolate those patterns. Another approach is to discover how a series depend on other variables, which serve as predictors. This set of exercises focuses on the first approach, while the second one Related exercise sets:

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Forecasting: Time Series Exploration Exercises (Part-1)

April 10, 2017
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Forecasting: Time Series Exploration Exercises (Part-1)

R provides powerful tools for forecasting time series data such as sales volumes, population sizes, and earthquake frequencies. A number of those tools are also simple enough to be used without mastering sophisticated underlying theories. This set of exercises is the first in a series offering a possibility to practice in the use of such Related exercise sets:

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Correlation and Correlogram Exercises

April 8, 2017
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Correlation and Correlogram Exercises

Correlation analysis is one of the most popular techniques for data exploration. This set of exercises is intended to help you to extend, speed up, and validate your correlation analysis. It allows to practice in: – calculating linear and nonlinear correlation coefficients, – testing those coefficients for statistical significance, – creating correlation matrices to study Related exercise sets:

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