I was actually pulling for the Niners yesterday primarily because I've lived in the SF Bay Area since 1999; but on balance, I didn't really care about the game: the Pixburgh Stillers weren't playing.
That and because the NFL actively supported SOPA, the bill that aims at restricting our internet freedom:
That said, here's a look how scatter plot of score vs game duration.
Source data: Milwaukee-Wisconsin Journal Sentinel
The awesome thing about Excel is that you get to change the Y-axis increments (I made it 7 since that's how many points are in a touchdown)... as well you can configure the X-axis increments (I made it 15 since that's how many minutes are in a quarter).
It's a nice graph and all, but not terribly reflective of what actually happened. You can see from the start of the game, there's a ramp from 0 to 7 for the Baltimore Ravens. That's not what actually happened. At 4:23 into the first quarter, the score was still 0. At 4:24, the Ravens' score was 7.
Let's look at what this graph looks like in PI ProcessBook with correctly configured tags:
Here, is an accurate depiction of what the scores were at the time they happened: the score goes up in increments forming what looks like "steps".
When you have infrequent data, the most accurate visual representation of the data is to set the step point attribute equal to one (step=1). For cell culture and fermentation, you do this for any offline measurement such as:
That and because the NFL actively supported SOPA, the bill that aims at restricting our internet freedom:
That said, here's a look how scatter plot of score vs game duration.
Source data: Milwaukee-Wisconsin Journal Sentinel
The awesome thing about Excel is that you get to change the Y-axis increments (I made it 7 since that's how many points are in a touchdown)... as well you can configure the X-axis increments (I made it 15 since that's how many minutes are in a quarter).
It's a nice graph and all, but not terribly reflective of what actually happened. You can see from the start of the game, there's a ramp from 0 to 7 for the Baltimore Ravens. That's not what actually happened. At 4:23 into the first quarter, the score was still 0. At 4:24, the Ravens' score was 7.
Let's look at what this graph looks like in PI ProcessBook with correctly configured tags:
Here, is an accurate depiction of what the scores were at the time they happened: the score goes up in increments forming what looks like "steps".
When you have infrequent data, the most accurate visual representation of the data is to set the step point attribute equal to one (step=1). For cell culture and fermentation, you do this for any offline measurement such as:
- viable cell count
- viability
- offline pH
- Osmo
- Glucose, Lactate, Ammonium, Sodium
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