How would one set up a Difference of Means test to test the relationship between type of electoral system (IV) and type of party system (or number...

A Difference of Means test, also called a t-test, is one of the simplest statistical procedures, yet also one of the most widely used because of its broad applicability. It's especially useful in controlled experiments, where the two means being compared are the control group and the experimental group.

Difference of Means requires a categorical variable for the independent variable, and a quantitative variable for the dependent variable. The categorical variable should have only two options (for more categories, you can use a chi-square or F-test).

Here our independent variable is the electoral system, which is clearly categorical; there are multiple types to consider, but the two big ones are "first-past-the-post" plurality vote (like the US) and proportional representation (like Sweden). So we would make those our two categories, and sort countries into each group. If a country is hard to fit into either category (such as "mixed member proportional representation" in Germany), we might want to just leave it out of this analysis.

Then we need a variable to measure the party system, which must be quantitative---so that we can calculate a mean. The number of major parties would probably be a good one to use, where we could define "major" somehow, perhaps as having won at least three seats in the legislature or at least one election of the executive. (This would give the US 2 parties and Sweden 8 parties.) As a robustness check, we might want to see what expanding or contracting the definition of major parties does to our results.

Then, we just compute the mean number of parties among all countries in each category, as well as the standard deviation in each; the basic t-test is just to take the difference of the two means and divide it by the standard error, where the standard error is the average of the standard deviations, divided by the square root of the sample size.

This value we call t, and we can look it up on tables of the t-distribution to see how probable it is that a difference of this size would occur by chance.

Is there a word/phrase for "unperformant"?

As a software engineer, I need to sometimes describe a piece of code as something that lacks performance or was not written with performance in mind. Example: This kind of coding style leads to unmaintainable and unperformant code. Based on my Google searches, this isn't a real word. What is the correct way to describe this? EDIT My usage of "performance" here is in regard to speed and efficiency. For example, the better the performance of code the faster the application runs. My question and example target the negative definition, which is in reference to preventing inefficient coding practices. Answer This kind of coding style leads to unmaintainable and unperformant code. In my opinion, reads more easily as: This coding style leads to unmaintainable and poorly performing code. The key to well-written documentation and reports lies in ease of understanding. Adding poorly understood words such as performant decreases that ease. In addressing the use of such a poorly ...

nouns - what do you call the person who passes the trophies to the prize giver/presenter?

The person who gives out the trophies to the winners are called award presenters. So what do u call the person who passes the trophies to the presenter? Thanks!

Is 'efficate' a word in English?

I routinely hear the word "efficate" being used. For example, "The most powerful way to efficate a change in the system is to participate." I do not find entries for this word in common English dictionaries, but I do not have an unabridged dictionary. I have checked the OED (I'm not sure if it is considered unabridged), and it has no entry for "efficate". It does have an entry for "efficiate", which is used in the same way. Wordnik has an entry for "efficate" with over 1800 hits, thus providing some evidence for the frequency of use. I personally like the word and find the meaning very clear and obvious when others use it. If it's not currently an "officially documented" word, perhaps its continued use will result in it being better documented.

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