Suppose we have a binomial experiment in which success is defined to be a particular quality or attribute that interests us. (a) Suppose n = 26 and p = 0.36. (For each answer, enter a number. Use 2 decimal places.) n·p = n·q = Can we approximate p̂ by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _____.) _____, p̂ _____ be approximated by a normal random variable because _____ _____. first blank Yes No second blank can cannot third blank n·p does not exceed both n·p and n·q exceed n·p exceeds n·p and n·q do not exceed n·q does not exceed n·q exceeds fourth blank (Enter an exact number.) What are the values of ?p̂ and ?p̂? (For each answer, enter a number. Use 3 decimal places.) ?p̂ = mu sub p hat = ?p̂ = sigma sub p hat = (b) Suppose n = 25 and p = 0.15. Can we safely approximate p̂ by a normal distribution? Why or why not? (Fill in the blank. There are four answer blanks. A blank is represented by _____.) _____, p̂ _____ be approximated by a normal random variable because _____ _____. first blank Yes No second blank can cannot third blank n·p does not exceed both n·p and n·q exceed n·p exceeds n·p and n·q do not exceed n·q does not exceed n·q exceeds fourth blank (Enter an exact number.) (c) Suppose n = 41 and p = 0.40. (For each answer, enter a number. Use 2 decimal places.) n·p = n·q = Can we approximate p̂ by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _____.) _____, p̂ _____ be approximated by a normal random variable because _____ _____. first blank Yes No second blank can cannot third blank n·p does not exceed both n·p and n·q exceed n·p exceeds n·p and n·q do not exceed n·q does not exceed n·q exceeds fourth blank (Enter an exact number.) What are the values of ?p̂ and ?p̂? (For each answer, enter a number. Use 3 decimal places.) ?p̂ = mu sub p hat = ?p̂ = sigma sub p hat =

Suppose we have a binomial experiment in which success is defined to be a particular quality or attribute that interests us. (a) Suppose n = 26 and p = 0.36. (For each answer, enter a number. Use 2 decimal places.) n·p = n·q = Can we approximate p̂ by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by ___.) _, p̂ _ be approximated by a normal random variable because _ _. first blank Yes No second blank can cannot third blank n·p does not exceed both n·p and n·q exceed n·p exceeds n·p and n·q do not exceed n·q does not exceed n·q exceeds fourth blank (Enter an exact number.) What are the values of ?p̂ and ?p̂? (For each answer, enter a number. Use 3 decimal places.) ?p̂ = mu sub p hat = ?p̂ = sigma sub p hat = (b) Suppose n = 25 and p = 0.15. Can we safely approximate p̂ by a normal distribution? Why or why not? (Fill in the blank. There are four answer blanks. A blank is represented by _.) _, p̂ _ be approximated by a normal random variable because _ _. first blank Yes No second blank can cannot third blank n·p does not exceed both n·p and n·q exceed n·p exceeds n·p and n·q do not exceed n·q does not exceed n·q exceeds fourth blank (Enter an exact number.) (c) Suppose n = 41 and p = 0.40. (For each answer, enter a number. Use 2 decimal places.) n·p = n·q = Can we approximate p̂ by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _.) _, p̂ _ be approximated by a normal random variable because _ ___. first blank Yes No second blank can cannot third blank n·p does not exceed both n·p and n·q exceed n·p exceeds n·p and n·q do not exceed n·q does not exceed n·q exceeds fourth blank (Enter an exact number.) What are the values of ?p̂ and ?p̂? (For each answer, enter a number. Use 3 decimal places.) ?p̂ = mu sub p hat = ?p̂ = sigma sub p hat =

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

(a)

Suppose n = 26 and
p = 0.36.

(For each answer, enter a number. Use 2 decimal places.)
n·p =
n·q =

Can we approximate p̂ by a normal distribution? Why? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)

_____, p̂ _____ be approximated by a normal random variable because _____ _____.

first blank

Yes

second blank

can

cannot

third blank

n·p does not exceed

both n·p and n·q exceed

n·p exceeds

n·p and n·q do not exceed

n·q does not exceed

n·q exceeds

fourth blank (Enter an exact number.)

What are the values of ?_p̂ and ?_p̂? (For each answer, enter a number. Use 3 decimal places.)
?_p̂ = mu sub p hat =

?_p̂ = sigma sub p hat =

(b)

Suppose

n = 25 and
p = 0.15.

Can we safely approximate p̂ by a normal distribution? Why or why not? (Fill in the blank. There are four answer blanks. A blank is represented by _____.)

_____, p̂ _____ be approximated by a normal random variable because _____ _____.

first blank

Yes

second blank

can

cannot

third blank

n·p does not exceed

both n·p and n·q exceed

n·p exceeds

n·p and n·q do not exceed

n·q does not exceed

n·q exceeds

fourth blank (Enter an exact number.)

(c)

Suppose

n = 41 and
p = 0.40.

Yes

second blank

can

cannot

third blank

n·p does not exceed

both n·p and n·q exceed

n·p exceeds

n·p and n·q do not exceed

n·q does not exceed

n·q exceeds

fourth blank (Enter an exact number.)

What are the values of ?_p̂ and ?_p̂? (For each answer, enter a number. Use 3 decimal places.)
?_p̂ = mu sub p hat =

?_p̂ = sigma sub p hat =

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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