# March 2015

## Net Present Value by first principles

Formulas discussed: NPV, XNPV

In a previous post we looked at how Excel calculates NPVs and IRRs and some of their weaknesses. In this post we’ll show you how you can manually calculate an NPV so that you have greater flexibility and control, and know exactly what kind of answer you’re getting.

The first part of the workbook is a refresher on how NPV and XNPV produce different results, based on their different assumptions of the start date. XNPV is useful if you are not dealing with constant, annual periods, and means you don’t have to separately calculate a discount rate for the particular period length if you start with an annual rate.

Net Present Value by first principles

## Nothing to hide, everything to fear – why metadata retention is bad for everyone

Australian government efforts to implement metadata retention laws are all over the news. If you read the newspapers or their websites, then you know that not even the Attorney-General seems to know what metadata will be collected, the Australian Federal Police says you have nothing to fear and they’re not interested in you, the government is only after terrorists, paedophiles and organised crime, and the data may or may not be used to see if you’re downloading movies. From the same sorts of sources, you’ll also know that the only possible problems with this regime are that journalists and whistleblowers might be more vulnerable, and that it will cost a lot of money to implement, even in this time of “budget crisis.”
Now don’t get me wrong, I can see why our law enforcement and intelligence agencies would like this bill implemented – if I can see a tool that will make my job easier, with no cost to me, I’d want it too. And yes catching terrorists and paedophiles (why does everything always come back to these two groups?) is a good thing. But just because you think spying on every citizen is a bad thing, does not mean you’re on the side of terrorists and paedophiles.

Nothing to hide, everything to fear – why metadata retention is bad for everyone

## The perils of data analysis – speeding fines and the road toll

Excel formulas discussed: Slope, Correl
SPSS formulas discussed: Correlation, Regression, Oneway

I was reading an article on CarAdvice recently that argued that increased speeding fine revenue in Victoria had done nothing to reduce accidents, and that in fact speed cameras were dangerous. The argument was that while deaths had decreased, safer cars had just transferred deaths into hospitalisations; accidents were continuing at roughly the same rate but the outcomes were better. Whilst I would tend to agree with a number of the statements regarding low-level violations (particularly as I recently copped a speeding fine on a motorbike when sunglare meant I couldn’t see the speedo for a minute, and I clearly misjudged engine sound), I thought that some of the logical steps and data analysis (or lack thereof) were worth looking into.
In making the claim that speed cameras don’t reduce the road toll, the article relied on the data in this graph.

The perils of data analysis – speeding fines and the road toll