#Condense calculator free#

Of course, as you know, the vibration of molecules depends on temperature: the higher the temperature, the faster the molecular vibrations, and the more likely a liquid water molecule will break free from its neighbors and evaporate into water vapor. To better understand how net evaporation and net condensation are achieved, we need to understand a bit more about what controls the evaporation rate (the number of water molecules evaporating in a given area over a given time period) and the condensation rate (the number of water vapor molecules condensing into liquid water in a given area over a given time period).įor starters, the bonds that loosely connect water molecules in the liquid phase aren't all that strong, so occasionally, the natural vibration of water molecules breaks these bonds, resulting in evaporation. The states of net evaporation and net condensation are extremely important to weather forecasters, because they have implications for cloud and precipitation formation, as well as evaporation of precipitation (and subsequent evaporational cooling) among other things. On the other hand, assuming you have some liquid water present to begin with, 'net' evaporation, which means that the evaporation rate exceeds the condensation rate, causes liquid water droplets to shrink (or disappear altogether), or puddles on the ground to dry up, etc. 'Net' condensation means that the condensation rate exceeds the evaporation rate causing liquid water droplets to form. Obvious phase changes occur when there's either 'net' condensation or 'net' evaporation (assuming you have some liquid water to begin with). (2010), The Cambridge Dictionary of Statistics, Cambridge University Press.In the last section, I asserted something that may have been surprising: evaporation and condensation are occurring around you simultaneously all the time, but you often don't see the results because they're happening on the molecular level. BMJ 2011 342 doi: (Published 11 March).Įveritt, B. Correlation in restricted ranges of data. The overall trend, however, was for the correlation coefficient to become smaller for restricted ranges. For BMIs between 30 and 35, there was practically no correlation (-0.09). When the range was restricted to BMIs over 35, the correlation coefficient was 0.86. However, the correlation differed for varying restricted ranges. In a study of diabetic patients, Bland & Altman (2011) found a strong correlation (r = 0.85) between waist measurement and BMI. Your results may simply be a product of this peculiar phenomenon.

Therefore, if you’re dealing with a restricted range and the correlation coefficient is small (or zero), you shouldn’t draw the conclusion that there isn’t a correlation. However, when the range is restricted to people who studied more (about 40 hours - to the right of the red line), the correlation coefficient goes down - to 0.72.įor this particular example, restricting the range to the left of the red line would reduce the correlation coefficient even further, to 0.50:Īlthough there is a very strong correlation overall (.91), this association is weakened to 0.72 and 0.50 when the range is split into two. Not surprisingly, the correlation coefficient is rather high: 0.91. The following image shows the correlation between hours studying and test scores.

In fact, when the range is restricted, a peculiar phenomenon happens: the correlation coefficient goes down.