Math Question (Basic)
 

Okay, I'm trying to figure out how somebody messed up a calculation in a report.

They claim that there are 363, 857 people in Year A, and 422, 495 people in Year B. They then say that the growth is 13.8 percent.

Okay, that's obviously not correct. But how did they come up with 13.8 percent? I'm trying to figure out if they mis-entered a number or if they can't do basic division or what the heck their problem is, but I can't even come up with a scenario that would produce 13.8 percent. Can anyone figure out how a person who's bad at math would come up with that answer?

13.8 percent of all statistics are made up. Maybe they just took a terrible guess.

You lost me around year B.

I ran all sorts of different computations into my calculator, and all I can come up with, is they took a wild stab at it.

This should be the simplest thing ever. I can't figure out how they screwed up, and I need to know.

(422495-363857)/422495

422,495-363,857=58,638

58638/422495=.13878

Dammit you beat me to it! I type too slow.. but in my defense I double checked my answer!

(of course I could delete your post and take all the credit :D)

I'm drinking Scotch. :p

Sadly.. even with bad math they rounded incorrectly... it should be a wrong answer of 13.9%

dammit, you win.

I agree with the n00b.

Ah! So they calculated population growth using the wrong denominator. Brilliant! Rep for everybody in this thread!*

*Only those posting prior to this post. One rep per person only. Rep not available in Vermont and Michigan.

These people are a bunch of idiots. They had no business doing this report that I'm reading, and the very first number in the report is this one, which is calculated wrong.

I did a report on Chiefs planet. Wanna read it?

:shake:

That's sad.

Does it contain figures on population growth?

The real tragedy is that with two data points they can't even be sure that they've selected the correct population growth model.

Obviously they chose a linear growth model:

dP/dt = k

But their estimates would be different if they had chosen a geometric growth model:

dP/dt = kP

or a decreasing rate of increasing progression model:

dp/dt = k (Z-P)

You'd need at least three data points to accurately select the correct model. Taken together the three models make the classic S-shaped population curve (Geometric -> Linear -> Decreasing Rate). Any of the three models might be applicable, depending on the amount of resources available relative to the population, demographics, and social attitudes. Also, none of these models should be used to project populations more than 10 years into the future.

Did they mention these factors in their report?

bam

Interesting. On population projections of humans, I've typically used either a simple exponential model (short-term only), or a ... what's it called. P2=P1*e^(-kt). That one. Can't remember the name. For population growth they tend to work pretty well because the growth rates are relatively small numbers.

What's Z in your third model?

I know this firm, and they have no ability to do projections at all. In fact, all they were trying to do is say that the population has grown X percent over a 7 year period, and they couldn't even do that.

This one particular firm is a joke. They don't do research and have no researchers on staff, but if a client wants it they'll make all sorts of claims and take their money. And then they do stuff like the calculations above. And don't even get me started on their surveys. I wish my business had some sort of entry requirements.

Yeah, well,
http://users.scnet.rs/~mrp/formula20.7.gif

P2=P1*e^(-kt) is the integrated form of the geometric model. Also called a first order model. I would also call it an exponential growth model.

In the third model, Z is the "maximum" population that the resources in the area would support. That model approaches Z asymptotically.

I always tell my students (we need to do population projections to build water and wastewater plants that have to have a useful life of up to 50 years) that population projections are black magic and to get someone else to do them.

I use the following in-class example. Rank the following cities in terms of their 1910 and 1960 populations, and describe the driving forces for the change in population over that time interval:

Providence, RI
Detroit, MI
Miami, FL

why is my brain hurting?

Because it is a differential equation world, and you're living in it.

I can't add or subtract fractions, and I scored very high on the GED. And I don't know much about the little numbers next to the big ones or wtf numbers in parentheses are for. (88)32>2, that makes no since.

Is it the gravity I brought to the conversation?

Interesting. I've never done a resource-constrained model, in part because no one ever thinks their resources are constrained. Well, almost no one. And honestly, I kind of agree. I think of it in terms of that bet those two professors made about the price of zinc or something, and the one who bet on lower future prices won - innovation will always beat limitations.

As one exception to my usual situation, I did a study to locate a facility in a resort town once, and they said to assume that population growth would stop in X years because they would be at their limit of developable space. After some arguing, I built it in, but I don't believe that for a second. The place was desirable, and densities will always increase in desirable area because people will build up if they can't find ground of their own. And governments won't stop it if they can get big fees out of it. I see the same thing in my neighborhood - some developer tore down three houses and put up two high rises that now have 75 or 80 units. Manhattan is an example of how growth limits really don't apply in the real world other than in extreme cases.

I agree with you that population projections can get blindsided by unexpected extrinsic factors on a local level if you're doing a 50-year projection. I've never done projections that far out, so I haven't really thought about it. I think in that case, though, you have to just assume historic rates of growth will continue (with some adjustments for things like urban growth patterns) and hope for the best.

As another war story related to extrinsic impacts, I was on a project a couple of years ago for a small rural county, and people were bashing some land planning firm for developing a population projection that seemed unfathomable to the locals - something like quadrupling over 50 years. I stayed out of the fight, but thought it was funny that the locals didn't take one thing into account. A large metro area had expanded to where the first suburbs were just spilling across this county's borders. Generally, once you start becoming a suburb, populations explode beyond all historic data. I think the land planning firm was probably right, but hey, they hire a competitor of mine for all their research so let them defend their own damned selves.

Let me guess the people who prepared this are broncos fans right?

probably in most cases. their turnover rate is so high that they probably get fans of all teams passing through, though.
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*dusts off TI-89*

*batteries dead*

It was DaFace, wasn't it?

as per the rounding error, depends on whose rules you use. some of the standard rules of rounding that I've come across from several sources state that you don't round up if the number is even, and round up with odd numbers (e.g. you'd round up 132.79, but not 132.69).

That only applies if the last digit is a 5. Example:

132.75 round to 132.8
132.65 round to 132.6.

In your example you should round both numbers up.

eh, guess I ignored that part. good catch.