What I am trying to do:

I want to find the maximum number of rentable rooms that could exist if someone wanted to either build am addition or construct a building in a specific city zoning district--in this case it would be up to 4 floors per parcel (or property).

I have a population data set for a City's zoning district which includes values for the number of apartments, building square footage, and total parcel square footage, but it lacks a value for the number of floors that exist for each of these properties. Using excel's data analysis addon I found the following descriptive statistic values which I used to find my minimum sample size of 245 for inspection in google maps to find the sample's number of floors.

(Based off of the population of rentable rooms)

Mean 8.623955

Standard Error 0.539443

Median 4

Mode 4

Standard Deviation 20.44196

Sample Variance 417.8738

Kurtosis 153.0291

Skewness 10.86511

Range 392

Minimum 3

Maximum 395

Sum 12384

Count 1436

Confidence Level (90.0%) 0.887878

Minimum sample size equation: n= (Zσ/E)^2

Total sample size with a deviation if the error is 1 = 245

(I'm not sure if I should change this value to 1 but if I use the standard error of 0.53 my sample size jumps to ~800 which was to large to do easily)

I've found that I'll need to use the median rather than the mean because of the skew a handful of large values lend to the descriptive statistics (maximum = 395).

What I am struggling with is finding out how to use this data to find the total number of rentable rooms.

What I have at the moment is:

Code:

```
( The upper and lower bound of the median / number of floors ) / building square footage = the range of rentable space for one floor by sqft
After this I use the ( lower and upper range of rentable space by sqft for one floor * each buildings square footage in the population ) * 4 floors
```

I'm sort of at a loss at this point on what to do.

If anyone can offer some advice in laymens terms that'd be super!