Atlanta Database Programmers

Oh, the NES. As an ’89 baby, there wasn’t a larger part of my childhood than this gaming console. Before school, after school, and on weekends you would find me attached to this thing. With Crystalis, Metroid, Metal Gear, Final Fantasy, Mega Man 1-6, Castlevania, Dragon Warrior, River City Ransom, Mike Tyson’s Punch-Out!!, Contra, The Legend of Zelda, and the entire Mario Bros. series, what is there not to love as a kid? The NES wasn’t the first console, but it was the one that really cracked open the world of gaming and brought it to the forefront of home entertainment.

In this article, you’re going to learn how to re-live and enjoy those amazing classic games on your computer using Nestopia.

Downloading Nestopia

Nestopa is no longer being actively developed. It doesn’t need to be either, it’s practically perfect as it stands!

There are versions of the software available for the Windows, Linux, and Mac platforms. Here are direct links to the latest version (1.40):

• Windows
• Linux
• Mac

Nestopia is also open source! You can find the source code here. Nestopia is portable, so it can be thrown onto a service like Dropbox or a flash drive and go with you.

Configuring Nestopia

“Out of the box,” Nestopia doesn’t require too much advanced configuration. It’ll work just fine after unzipping the archive. However, I do recommend going into the Preferences… beneath the Options menu.

Here, just go ahead and check the boxes beside each file association. It’ll make loading ROMs a lot easier for you in the future.

Other than that, you can familiarize yourself with the controls at the Input… screen, also under Options.

The controls are pretty simple by default: directional keys for the directional pad, comma and period for A and B, and then Enter for the Start button.

Getting ROMs

CoolROM is the only website I’ll recommend that you download your NES ROMs from.

Please be advised that you are only legally allowed to download ROMs if you own a license for any and all that you download and you will not distribute or attempt to profit from the ROMs. I’m not going to spew any more legal mumbo-jumbo because the emulation sites themselves should have their own disclaimer. You should know what not to do.

Download and extract the ROMs into the same folder. It’ll get messy and confusing otherwise. NES ROM files have the “.nes” extension.

Loading ROMs

Loading your games is as easy as can be. Simply go to File and then Open… and navigate to the location where your ROMs are stored.

If you made the file associations that I recommended before, you can alternatively just browse to the folder in Windows Explorer and double-click the file. It’ll automatically load and start in Nestopia.

Saving States

This sure does beat having to remember a 16-digit password or having to play through 10 minutes of gameplay just to reach a stopping point. Nestopia supports the saving of your states, which is basically instantly saving your game progress.

All you’ve got to do is go to File and then Save State…. Load State… will allow you to restore your progress.

Go now. You’ve got time to waste and an entire childhood to catch up on. Or if you’re one of our younger readers, how about you go enrich yourself in some real gaming with Nestopia!

If you’re a Super Nintendo fan, I did a very similar article on how to emulate SNES games using ZSNES. Go check it out and let’s talk some NES in the comments here!

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According to the 2011 Marketing Sherpa Landing Page Optimization Benchmark Report, 40% of the over 2,000 marketers surveyed did not calculate the statistical significance of A/B and multivariate test results in 2010. 40%! That’s a big chunk of marketers.

Clearly, validating your test results should be a key part of the conversion testing process, or you’re going to be acting on bad data (and losing cash).

But how can you tell when there might be problems with your numbers? Look out for these 4 types of validity threats:

Too small a sample size

To find a winner, test your layout and copy variations with enough test subjects to reach a high level of confidence in your results. But how many is enough? Several factors impact the sample size you’ll need including:

• The current conversion rate of the page you’re testing (note: not the same as the conversion rate of your entire site)
• The average number of daily visits to the test page
• The number of versions you’re testing
• The percentage of visitors in the experiment (sometimes you want to test with just a segment of your traffic)
• The percentage improvement you expect over the control
• How confident you need to be in the results (usually 95% but could be higher if the risks of being wrong are high)

To estimate how long you need to run your test for your results to be statistically significant at the 95% confidence level (i.e. 5% chance you’ll think the variations are performing differently when really they aren’t), look to the Google Website Optimizer calculator. Amadesa also has an A/B experiment duration calculator that’s little more flexible. It lets you choose the level of confidence you want to achieve. By playing with the calculators, what you’ll find is that if your site gets limited traffic, you won’t be able to run as many versions or segment your test traffic as much as a higher volume site.

Multiplying the potential duration of your experiment by your average daily visitors gives you an indication of your sample size (or you can use a complicated formula). It’s helpful to have a sample size in mind before you start testing because many testing tools can be a little misleading. They can turn “green” or “red” after only a few visits, falsely indicating a high level of confidence that you have a winner or loser, and then quickly revert back to “yellow” or inconclusive results. If you heed the first “green” bar, you will stop your test too early. By waiting until you’ve tested with your full pre-determined sample size, you stand a better chance of finding the real superior performer. But don’t worry, peeking during a test is ok, and necessary as we’ll see below.

An external event that changes visitor behavior

Events outside of an experiment, often called “history” threats, can affect response rates. Often, these are news events (e.g. holidays, major industry or company events, or news stories) that significantly but temporarily affect the attitudes and behaviors of visitors, and the amount of traffic. So much so that you can’t tell whether response differences are due to page changes or the historical event.

This is why we never recommend sequential testing, like trying one page version against your control in the first half of the month, and another version in the second half. An external event that happened only during the second half of the month can alter your results. But even A/B split testing is susceptible to external influencers. While an external event impacts all test versions equally, your overall results may vary if you had started the test earlier or later.

To minimize the risk of “history” impacts, here are a few tips:

• Regularly analyze your data for consistency during the test, especially if it’s particularly long running.
• Don’t run tests that extend into holidays (or across periods that differ significantly for your industry) unless holiday behavior is what you want to study in your test.
• During the test, look out for industry or news stories that may temporarily affect purchase behavior or traffic.
• Test over a longer duration, or repeat a test (to a point), until you are confident in your data.

A change in your technical environment or measurement tools

“Instrument change”, where something happens to the technical environment or the measurement tools used during a test, can invalidate the results of your A/B or multivariate experiment. This could be things like:

• Inconsistent placement of test control code (e.g. in the body on some pages but in the header on others)
• A code deploy happening during a test that disables or alters your control code
• Performance issues stemming from web server or network problems
• Testing software or reporting tool malfunction
• Response time slowdowns due to heavy page weights or page code, or server overload

While your test is running, if you spot sudden changes in performance or traffic distribution between variations, take a look under the covers to see if your technical environment or testing toolkit has altered in any way.

And to reduce the risk of “instrument change”, follow these guidelines:

• Make sure your control code is placed correctly and consistently across all your versions.
• Browser compatibility check your versions before launch to make sure there are no compatibility issues.
• Be careful when deploying code while a test is running not to alter or delete your test control code.
• Monitor for odd data during the test. If you have multiple sources of the same data, cross check your numbers every once and awhile to make sure there are no major differences.

A change in incoming traffic sources or traffic mix

When different types of visitors are not distributed equally between page versions, the test outcome can be affected. This is called “selection bias”. For example, if your incoming traffic sources, or mix of traffic, change dramatically during the test (due to a big email send or other channel-specific marketing activity). Or if the profile of your testers doesn’t match the profile of your actual customers.

While your test is running, monitor your control to make sure it’s not deviating significantly from past performance. As with “instrument change” threats, look out for sudden changes in the performance of one page version over another, or in the distribution of traffic amongst your variations.

Here are a few ways to minimize “selection bias”:

• Use traffic sources that most closely match the target audience for the page being tested.
• Make sure visitors are being randomly distributed between your test versions. It should be impossible for you to predict which version a given visitor will see, and visitors shouldn’t be able to self-select the version they see either.
• Compare the performance of your control with its recent historical performance for consistency.
• Gather enough analytics data to allow deeper analysis post-test. For example, to compare weekend vs. weekday results, or new vs. returning visitors.

And finally, always take time to carefully analyze your data after each test has run its course. Sometimes you’ll uncover interesting learnings like one variation worked better for one audience, while another worked better for a different group. Running follow-up tests can confirm these findings.

Looking for help with A/B and multivariate testing? Contact the Elastic Path consulting team at consulting[at]elasticpath.com to learn how our conversion optimization services can improve your business results.

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