P(<100) = P((new or change) & <100) = P(new & <100) + P(change & <100)
... = P(<100 | new)*P(new) + P(<100 | change)*P(change)
... = 0.90*0.70 + 0.20*0.30
... = 0.63 + 0.06 = 0.69 . . . . probability of completing a transaction in < 100 ms
A.) according to the graph, Austin appears to be burning 10 calories per minute. If you look at a perfect point on the graph, which I chose (50,5) and you do x over y or calories per minute, you get a unit rate of 10 calories per minute.
b.) Since you have already found the unit rate in question a, your slope would be 10.
Answer:
If the null hypothesis is true in a chi-square test, discrepancies between observed and expected frequencies will tend to be small enough to qualify as a common outcome.
Step-by-step explanation:
Here in this question, we want to state what will happen if the null hypothesis is true in a chi-square test.
If the null hypothesis is true in a chi-square test, discrepancies between observed and expected frequencies will tend to be small enough to qualify as a common outcome.
This is because at a higher level of discrepancies, there will be a strong evidence against the null. This means that it will be rare to find discrepancies if null was true.
In the question however, since the null is true, the discrepancies we will be expecting will thus be small and common.
I'm not quite sure what you asking here but if your asking how to answer it in "math terms" than I'll be happy to explain :)
So "times" means multiply and "increase" means add so righting this in math terms would be
6x + 5
because it's six times "a number" which you can replace with x!
Let me know if you have any questions :3
