Phoenix the Vizsla

Saturday, August 05, 2006

The Phoenix Growth Curve

The scientist in me likes to take data and analyze it. Earlier this week in lab, I was conducting a very standard microbiological test called a "growth curve" to characterize a new bacterium we have. It involves starting a culture at a low concentration of bacteria, letting the bacteria grow and measuring the concentration of the bacteria at various timepoints during the day. Bacteria have a very well defined time course with multiple phases of growth (lag, exponential, stationary). For more information you can look at the wikipedia entry on bacterial growth. I became interested to see if Phoenix was in exponential growth. So, I plotted his weight measurements over the past few vet visits and fit the data with a linear and an exponential curve. As it turns out, it appears he is in exponential growth (look at the R^2 values-- closer to 1 means a better fit!). I'll have to take more datapoints to confirm that though. It looks like he'll reach full size between 4 and 6 months. Perhaps the linear model is more correct since vizsla pups don't usually reach full size until closer to 6 months.

Yes, I am a scientist...

3 Comments:

At 6:19 AM, Anonymous Anonymous said...

For what its worth, my Vizsla Silenus, just turned 9 months old. Has only stopped growing in height but will still fill out more over the next few months, to become stockier.

He is at 23kg now. Only grew one kilo in the last month. Not a scientist myself so can't remember the term I'm thinking off for his growth chart. Probably an inverse exponential chart where you see a reduction in growth over time until you reach a plateau.

 
At 9:08 PM, Blogger Phoebe said...

Wow. Nice chart. Cody's 51 lbs now, but he gained 3 pounds in the last month (He's 8 months now). I really hope he stops soon (though if I become successful in asserting dominance, it won't matter if he's 200 lbs...)

 
At 10:33 PM, Anonymous Anonymous said...

you need more than 4 data pts. do you really think you can distinguish between the models based on so little data?

 

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