## Monte Carlo Methods in Excel: Part 2 – Random Numbers

Monte Carlo Methods in Excel: Part 2 – Random Numbers All Monte Carlo methods rely on a source of random numbers. Most such sources would more precisely be called pseudorandom numbers, since a deterministic algorithm cannot, by definition, ever produce truly random numbers. If you Google “random numbers” you will encounter a daunting list of […]

## Monte Carlo Methods in Excel: Part 1 – Introduction

If we toss a coin 1000 times, it is pretty easy to calculate the probability of tossing exactly 537 heads. For better or for worse, the real world rarely offers us such cut-and-dry calculations. What if we were trying to calculate neutron density in a critical mass of plutonium? A mathematically precise result is beyond […]

## How to apply Logistic Regression using Excel

Logistic regression is one of the most important techniques in the toolbox of the statistician and the data miner. In contrast with multiple linear regression, however, the mathematics is a bit more complicated to grasp the first time one encounters it. We’re going to gain some insight into how logistic regression works by building a […]

## Why Should You Pursue a Microsoft Certification?

If you’re considering taking a Microsoft Official Curriculum course (or your company is considering sending you to one) you should know that it’s a good choice for both of you. The most obvious benefit of taking a Microsoft Official Curriculum (MOC) course is that you’re getting information about Microsoft technologies from the source. Coupled with […]

## Awesome Way To Log in Power Query M Using Diagnostics.Trace

Several authors have described how to use the M function Diagnostics.Trace to monitor the performance of queries built with Power Query. In this installment, we will look at how to use the same function to record row-level error information in the trace log. Regardless of how we intend to use Diagnostics.Trace, nothing at all can […]

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