Constant Probability

[This is a completely different way of looking at the data than the previous section - ignore

conditional probability here. Just split your data into the first and second 35 trials.]

Using only the first half of your trials, find the point estimate for p. Use this to create a 90%

confidence interval for p.

Using only the second half of your trials, find p. Use this to find a 90% confidence interval for p.

Graph both intervals on a number line and compare them. Do they overlap?

Number line

0.40

0.45

0.50

0.55

0.60

0.65

-0.5

-0.4

You can use Wolfram | Alpha for this. To get the graph here, I typed "plot interval

(0.5,0.68) and (0.4,0.58)."

Do you think the probability of a success was constant throughout your trials? Explain why or

why not, based on the statistical results you found and any other reasoning you have (as before,

it is impossible to prove the two are equal, but you may be able to conclude that they are not

equal).

Note that this is only one way at looking at constant probability - we could also choose to split

up the trials by even/odd, for instance - so it's certainly incomplete. If you have other reasons to

think the probability isn't constant, you should include them.

Extra Credit (up to 3 points):

Perform a hypothesis test, with a = 0.10, comparing the probabilities from your

first and second 35 trials (call these p₁ and p₂). Use as your null hypothesis p₁ =

P₂.