# Tips & Tricks

Latest tips, movie demos, white papers and more available for all of our products. Learn how to use NumXL and all of our products more efficiently and accurately. Discover how to use all of our products to their full potential.

##### Text Book Example - Airline Passenger Data

In this issue, we present the analysis, modeling and forecast for international airline passenger data. We make use of a familiar example that first appeared in Time Series: Forecast and Control, a textbook by Box, Jenkins and Reinsel, originally published in 1969.

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##### Sales Forecast Example - Models comparison and selection

In this paper, we will apply econometric techniques to build a 6-month forecast for a sales force at company X. For sample data, we will use the monthly total sales figures for the last 25 months. Our objective is to compare competing models and to define a guideline for selecting the best model.

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##### NumXL Cookbook - Volatility Forecast With GARCH

In this paper, we will demonstrate the few steps required to convert the market index S&P 500 data into a robust volatility forecast using the NumXL Add-in within Excel

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##### NumXL Cookbook - GLM with Binary Data

In this tutorial, we will use a sample data gathered during a clinical trial of a new chemical/pesticide on tobacco Budworms.Our objective here is to model (and forecast) the effectiveness of the new chemical pesticide using different dosages, and explain, to some extent, any effect variation based on the gender of the budworm.

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##### NumXL Cookbook - AirLine Model

In this document, we start with historical residential electric power demand (monthly) between Jan 2003 and Dec 2010. Next, we demonstrate the minimal steps needed to process the time series, and fit a special seasonal ARIMA model - AirLine model - to the data, and construct a statistical forecast for the following 24 months using only NumXL.

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##### Normality Test - Facts and Myths

In this paper, we will use NumXL to carry out three different normality tests - the Jarque-Bera, the Shapiro-Wilk and the Anderson Darling - to examine the sensitivity of each test in detecting deviation from normality for different sample sizes. For sample data, we will generate 5 series of random numbers, each from a different distribution. The objective of this exercise is to demonstrate the strengths of each test, and to provide a tutorial for using the NumXL Normality Test function.

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