NumXL 1.64 offers various tools for conducting complicated analysis in Microsoft Excel. NumXL 1.64 now offers periodogram, automated subscription updates, and Spanish localization.
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Hello and welcome to the Introduction video to NumXL 1.64.
After installing NumXL 1.64, the software adds a separate tab your Microsoft Excel with loads of shortcuts to common and advanced functionalities that will make your modeling and forecasting tasks a lot easier.(Add shadow Box)NumXL operates on your sample data both in the time domain
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and in the frequency domain.
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In the NumXL 1.64 Descriptive Statistics button you can find various functions, like the empirical distribution function and the kernel density estimation function.
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In the Statistical Tests button, you will find statistical tests like the normality test, stationary test, and more.
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You can also find several linear time series models under the ARMA button.
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(show expanded menu of ARMA Models)
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You can also access our functions through the excel functions toolbar.
NumXL also offers hundreds of worksheet functions for your use.
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Each function is backed up with full documentation in the help file that comes with your NumXL software.
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You can also visit our online help desk at support.numxl.com.
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Our support website contains several tutorial videos and many tips to help you make the most of NumXL.
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We are constantly growing our set of tutorials, so make sure to check it out!Scene: user-guide
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The support website is a one-stop solution for all NumXL documentation and resources.
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Support.numxl.com also has an extensive frequently asked questions section where you can find an answer to virtually any question you may have.
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Furthermore, NumXL is designed with your needs in mind, so if you have an idea, tip, or a feature request please post your feedback in the community boards.
If you have any additional questions, issues, or concerns, you can always contact us by phone or email.
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Now, let’s take a look at some of the things NumXL has to offer.
NumXL contains numerous tools to help you understand your data.
In NumXL, you can compute your data’s summary statistics and visualize your data’s empirical distribution.
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Plotting a QQ-Plot can’t be any simpler than with the NumXL Wizard.
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Do you want to find out if your sample data is just plain noise, also known as uncorrelated data?
No problem, NumXL provides a series of statistical tests to answer this question and other questions about your data.
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We picked statistical tests that are the most relevant to your analysis.
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Using the NumXL Correlogram Wizard, you can examine the serial dependencies in your sample data within seconds.
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NumXL also supports a wide range of linear time series models including ARMA, ARIMA, SARIMA, AirLine and US census X12 ARIMA methodology.
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Each model comes with a simple Wizard that guides you through the whole process.
The wizard generates the different calculations and formulas right into your Excel worksheet.
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In just few clicks, you can use the US census supported program X12 ARIMA. This tool empowers you to conduct sophisticated modeling and analytics such as the X11 seasonal adjustment.
NumXL does all the hard work behind the scenes, so you don’t have to worry about any messy calculations
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For performing volatility modeling, you can use GARCH, exponential GARCH, and GARCH in the meant o capture volatility dynamics in time series data and other data.
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Starting with version 1.63, NumXL fully supports time series and Monte-Carlo simulations.
You can deploy these simulations using an easy-to-follow wizard or several worksheet functions.
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With this functionality, you can conduct scenarios and/or all types of ad-hoc analysis right in your Excel worksheet.
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In addition to ARMAX, NumXL supports a wide range of factor analysis models, for example NumXL implement linear regression modeling: This tool fills a large gap left by Excel’s version of regression.
With NumXL’s Regression, you can experiment with various models, examine any residuals, and overcome several regression problems faced by professionals
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Your arsenal of NumXL Tools also includes stepwise regression that can help you find the optimal set of input variables for your model.
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NumXL also uses leverage statistics and Cook’s distance for conducing influential data analysis.
With these two powerful tools, you are in a better position to identify data points that make might make your analysis biased.
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The principal component analysis (aka PCA) is also available in the 1.6 version of NumXL.
With PCA you can linearly transform a set of correlated data into uncorrelated factors and while using a subset of the uncorrelated factors, you can transform them into the original data set.
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All NumXL functions are accessible through your worksheet, and many of them don’t have their own wizard yet.
For instance, NumXL supports a wide range of time series smoothing functions such as WMA, simple, double, linear and triple exponential smoothing and trend functions.
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In the spectral analysis section, NumXL provides the discrete Fourier transformation (DFT) and its inverse, for any time series size or length.
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Starting with 1.64, NumXL include a new analysis wizard to construct a periodogram plot and identify key frequencies (if any) embedded in the time series.
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With this wizard, you don’t need to manually pre-process your data and remove any deterministic trend or stochastic drift (aka random walk).
Instead, the “Auto data treatment” functionality in the wizard will conduct a series of augmented dickey-fuller tests (aka ADF) for stationarity conditions, and if needed, apply the best treatment.
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Finally, NumXL include a number of utilities functions needed by serious analyst, for example, the interpolation and extrapolation Function.
Currently, NumXL supports four methods for interpolations: Forward flat, backward flat, linear and cubic spline The NumXL team works hard to constantly update the software and provide you with different functions that you’d need during your data analysis.
We encourage you to take advantage of NumXL tools, and don’t hesitate to call our customer support service.
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That’s it for now, thank you for watching.
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