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Suppose we have a binomial experiment in which success is defined to be a particular quality or attribute that interests us
Suppose we have a binomial experiment in which success is defined to be a particular quality or attribute that interests us.
(a) Suppose n = 39 and p = 0.13. (For each answer, enter a number. Use 2 decimal places.)
n·p =
n·q =
Can we approximate p? by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)
_____, p? _____ be approximated by a normal random variable because _____ _____.
first blank
Yes
No
second blank
can
cannot
third blank
n·q does not exceed
both n·p and n·q exceed
n·p does not exceed
n·p exceeds
n·q exceeds
n·p and n·q do not exceed
fourth blank (Enter an exact number.)
What are the values of μp? and σp?? (For each answer, enter a number. Use 3 decimal places.)
μp? =
mu sub p hat =
σp? =
sigma sub p hat =
(b) Suppose n = 25 and p = 0.15. Can we safely approximate p? by a normal distribution? Why or why not? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)
_____, p? _____ be approximated by a normal random variable because _____ _____.
first blank
Yes
No
second blank
can
cannot
third blank
n·q does not exceed
both n·p and n·q exceed
n·p does not exceed
n·p exceeds
n·q exceeds
n·p and n·q do not exceed
fourth blank (Enter an exact number.)
(c) Suppose n = 41 and p = 0.15. (For each answer, enter a number. Use 2 decimal places.)
n·p =
n·q =
Can we approximate p? by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)
_____, p? _____ be approximated by a normal random variable because _____ _____.
first blank
Yes
No
second blank
can
cannot
third blank
n·q does not exceed
both n·p and n·q exceed
n·p does not exceed
n·p exceeds
n·q exceeds
n·p and n·q do not exceed
fourth blank (Enter an exact number.)
What are the values of μp? and σp?? (For each answer, enter a number. Use 3 decimal places.)
μp? =
mu sub p hat =
σp? =
sigma sub p hat =
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