*Let me begin this rather lengthy report by thanking the guys and gals over at Rockstar Finance for putting together the massive directory, without which this report would not be possible. I have quite the love of all things numbers – perhaps this is what fuels my accounting obsession – and the moment I saw the Rockstar Directory it was obvious what needed to be done.*

*Due to the length of this post, it will be broken down into a series of posts. (Also because it takes a lot of time to verify the proper use of statistical methods) My hope is that you receive as much information and enjoy this as much as I do.*

**Preface**

As I began this report, it was extremely difficult to find a focus. The Rockstar Crew has compiled quite a bit of information and there are multiple different ways to view this data. Practically every field on the Rockstar Directory could become the focus. Location. Age. Sex. Family Status. Profession. Net Worth.

So, in an effort to provide a purpose this report will first focus on the broad category (i.e. percentage of blogs by state, or percentage of bloggers by sex).

After that breakdown, we’ll see how the reported Net Worth factors into this. (i.e. 20 year olds represent 23% of those surveyed, yet they comprise only 8.17% of the total Net Worth)

If possible, a correlation will attempt to be drawn between the specific category and the reported Net Worth.

Now, I’m not a statistician, so by all means if there is a fault in this logic – please let me know so it can be corrected!

So without further ado, let’s dive in!

**Introduction**

At the time of this writing, April 12, 2017, the Directory housed information on 936 respondents.

Note that participators were not required to complete all fields. Therefore, we have the following totals:

Unfortunately, the main topic of this report (Net Worth) also had the least responses. The total net worth reported in this survey was $124,715,485.74 between only 257 respondents – an average of $485,274.26.

**State/Province**

**Field Responses:**862**Percent of Total Responses:**92.1%**Unique State/Provinces:**128

The State/Province with the highest concentration is California, with 80 (9.2%) responses.

Knowing that, it isn’t surprising to hear that 50% of the total Field Responses are located in 10% of the States/Provinces. In other words, 451 responders are concentrated in only 13 unique locations.

12 of those 13 locations are US States, and the other location being Ontario, Canada.

Because 700 of the 862 (81.2%) responses are from the United States, this section of the report will focus on those states. There is not enough data to draw conclusions on the individual provinces from other countries.

Figure 1 shows the distribution of responses across the United States. Excluded from this graphic are those responses that were generalized geographical areas i.e. “Southeast”.

**Location and Net Worth**

It’s well known that location and income are closely linked – see Huffington Post and NY Times. This rise in income can be attributed to higher cost of living. Theoretically, 30 year old living in California should have a larger income than a 30 year old working the same job in Alabama. However, their net worth should be comparable because of the higher costs in California.

But that’s in a perfect world, for an average person. This isn’t a perfect world, and the respondents to this survey – like you – are actively studying and practicing how to lower debt and improve net worth; and are therefore not average.

Knowing this, should it be expected that net worth be independent of location – as in the perfect world?

Of the original 862 respondents, only 183 reported their Net Worth. In total, these 183 responses had a net worth of $102,578,196.27 which averages to $480,465.

If net worth was independent of location, would it not be expected that the average per respondent would fall roughly near that $547,087.78 value?

The table below shows the breakdown, by state, of the reported net worth.

As another visual, the data is graphed with the average of $547,087.78 shown as the horizontal red line. It becomes easier to see what is below this average, but what does it mean?

From this data, it’s not easy to see the correlation of the two variables (location and net worth) . Sure, of the 34 states, 28 of them are below the average. Statistically, this doesn’t mean anything though. After all, the large range of the data set (-$216,152 to $1,331,618) highly skews the average.

In order to determine if the net worth is independent/dependent on location the Chi Square Test will be used. Without diving into the math behind it, the Chi Square test returns a value 0 to 1 that represents the probability that a null hypothesis is true.

Simply put, the null hypothesis “proposes no statistical significance exists in a given set of observations”.

In our scenario, the null hypothesis is that the net worth of an individual is independent of the location.

Also, due to the small number of responses, the data will be pooled into the four major geographical regions defined by the IRS. The data breaks down to the following:

If the null hypothesis is true, then the expected values can be generated to simulate the situation that net worth is independent of location and is therefore random.

Following that, the expected values for this data set is generated:

It can be seen that the data is distributed in such a way that the columns and rows totals are the same as the actual values, however the data is more evenly distributed.

Excel’s CHISQ.TEST function is extremely convenient here, and results in a P-value of 0.69.

A P-value greater than 0.05 means the null hypothesis can be accepted. In this case, it is confirmed that for the data set net worth IS independent of location.

As stated before, this shouldn’t be surprising because many of the participants in the study are working to lower their debt, secure financial independence, secure retirement, or a combination of the above. With that in mind, the location should have less of an effect on a respondent’s net worth.