|
|
|
||||
|
|
|||||
Example 5.4 can be solved with the bitesti command. We supply the value of n k and p. We see the probability that X <= 1 is .7361, as shown in the book.
bitesti 10 1 .1
N Observed k Expected k Assumed p Observed p
------------------------------------------------------------
10 1 1 0.10000 0.10000
Pr(k >= 1) = 0.651322 (one-sided test)
Pr(k <= 1) = 0.736099 (one-sided test)
Pr(k <= 1 or k >= 2) = 1.000000 (two-sided test)
Example 5.5 also can be solved with bitesti. In this example, the N is 12, k is 5, and p is .25. Stata shows that the probability of missing 5 or more shots is .1576.
bitesti 12 5 .25
N Observed k Expected k Assumed p Observed p
------------------------------------------------------------
12 5 3 0.25000 0.41667
Pr(k >= 5) = 0.157644 (one-sided test)
Pr(k <= 5) = 0.945598 (one-sided test)
Pr(k <= 0 or k >= 5) = 0.189320 (two-sided test)
We can also solve example 5.7 using bitesti, as shown below. Stata shows the probablity X >= 1450 is .9802, as shown in the book.
bitesti 2500 1450 .6
N Observed k Expected k Assumed p Observed p
------------------------------------------------------------
2500 1450 1500 0.60000 0.58000
Pr(k >= 1450) = 0.980180 (one-sided test)
Pr(k <= 1450) = 0.021854 (one-sided test)
Pr(k <= 1450 or k >= 1550) = 0.043274 (two-sided test)
We can solve example 5.10 using bitesti as shown below.
bitesti 100 9 .1
N Observed k Expected k Assumed p Observed p
------------------------------------------------------------
100 9 10 0.10000 0.09000
Pr(k >= 9) = 0.679126 (one-sided test)
Pr(k <= 9) = 0.451290 (one-sided test)
Pr(k <= 9 or k >= 11) = 0.868135 (two-sided test)
We skip examples 5.11 and 5.12.
Show example 5.21 on page 416.
UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services