What Should I Expect From a GPS Logging Device?

What should I expect from a GPS logging device?

What Should I Expect From a GPS Logging Device? 1

I had a small tracker for a while and after faffing with it for a while sold it on eBay. So I may not be the best person to answer. But here goes.You need to decide on the basic parameters:That tells you how much battery life you need and how many data points you have to store. I would expect that the data points answer will be less than 10k. Battery life is what mattered to me in the end - I was uploading every few days and recharging when I did it. What ended up killing the idea for me was the lack of display on the thing. I wanted to be able to see how much battery life and memory it had left without plugging it into a computer. It could not do that.edit: for single-day use note that there are only 80k seconds in a day, and most small loggers need a second or so to take a reading. So a 30k point GPS could log every single second you were on your bike each day. More reasonably, logging every 10 seconds means at most 8600 points in 24 hours. So a 10k point logger will be fine.I think more important points will be GPS reliability, robustness and how waterproof it is. If you have to tape an antenna to the top of your helmet to get reliable reception that will suck, and likewise if it stops working because you went over a bump or through a creek. So I suggest looking at those features rather than focussing on battery life or data points. Work out where you want to mount it and run from there (in a backpack is quite different from in a pannier or handlebar bar, and different again from under the seat or on the handlebars

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In a pH titration why is it necessary to continue to take pH data points several mL of titrant beyond the...?

You want to make sure that you have reached a true end point. This is a particular problem when you titrate an acid with a base. CO2 in air is dissolving into water solutions all the time, forming carbonic acid. This small concentration of carbonic acid can make it appear that you've reached an end point. Then the color will go away as the CO2 dissolves into the solution. Often you can add several drops more before you get a solid and permanent color change. The key to successful titrations is always hitting the same color for all of your trials and as faint as possible. Also if you are using a pH meter to create a titration curve going past the end point make a nicer looking diagram.

What Should I Expect From a GPS Logging Device? 2

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Term for baseline with randomly distributed classes over same data points

Permutation tests are one of the resampling methods used in statistics. If you want to read more on such methods, you can check the introductory book Introduction to Statistics Through Resampling Methods and R by Phillip I. Good. You can also find an example in this thread

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What data points mobile DSP send along with bid request to ad networks?

Device os model Location (text form) * Location (geo coordinates) ** IP Application name Application's exchange ID Application's IAB content category Age/Date of Birth ** Supporting ad tags / standards ** Ad dimensions User ID (platform specific and not yet uniform) **

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Stationarity of cyclical economic data

First of all, just because there is an economic cycle in a data that does not imply that data is non-stationary. For example, consider the completely stationary process simulated in R below, which is based on $x_t = phi x_t-1 e_t$ with $phi=0.9$ which is stationary by construction yet it exhibits something like economic cycle. So the first thing you should do is to make sure there actually is non-stationarity in your data and not just assume that because data exhibit some sort of cycle. Either look in the literature on the given aggregate whether in general it is considered to be integrated of some order or perform your own unit root tests (assuming there is enough observations to carry them out - you dont mention if your data is on monthly, quarterly or yearly frequency. Depending on frequency there might be plenty of data points to carry out these tests even within the given years). Second, taking logs is not a solution for non-stationarity even if you have long time series (and I am not even sure what you mean by change percentages). The way how you solve non-stationarity is by taking differences of your data.For example, a simple non-stationary process is given by$$x_t= x_t-1 e_t$$The process is non stationary because $phi=1$ which implies that present variables are fully determined by initial conditions of the system and sum of shocks. If that is the case just taking logs of variables $ln x_t = ln x_t-1 e_t$ does not solve the unit root problem as you will have the same dependence and it does not matter how long your time series is. Taking logs of your variables can be desirable for many different reasons but not related to non-stationarity per se.What actually solves the non-stationarity/unit-root problem is to take first differences. For example, in the example above we could transform data as:$x_t -x_t-1= e_t$Which would become stationary series. You can apply the same procedure to $ln x_t$ but what ultimately gets rid of the non-stationarity is the differencing. In a worse case scenario you could have series that is integrated of order 2 in which case you would have to make one more second difference. However, eventually taking difference of the series will always produce stationary series. According to Verbeek (2008) guide to modern macroeconomics most economic series that are non-stationary are I(1) and in some rare cases I(2), so even with extremely short time series you should be able to make it stationary

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