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Solutions to Exam 2 of Math 220: Elementary Statistics by Kane Nashimoto (Fall 2006) - Pro, Exams of Statistics

The solutions to exam 2 of the elementary statistics course taught by kane nashimoto in fall 2006. It covers topics such as probability, normal random variables, correlation and regression, and binomial random variables. Students can use this document to check their answers, understand the concepts better, and prepare for exams.

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2019/2020

Uploaded on 11/25/2020

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Math 220 : Elementary Statistics Kane Nashimoto
Exam 2 Solutions
Fall 2006
1. Probability.
E:{selected student is male}
F:{selected student prefers morning classes}
Note : P(E) = .46 ; P(F) = .67 ; P(EF) = .29
(a) P(EF) = P(E) + P(F)P(EF) = .46 + .67 .29 = .840
(b) P(F|E) = P(EF)
P(E)=.29
.46 =.630
(c) P(at least one male) = 1 P(all female) = 1 (.54)3=.843
(d) P(EF) = .29 but P(E)P(F) = (.46)(.67) = .308
Two events are not independent.
2. Normal random variable.
Note : X, heating cost, is normal with µ= 450 and σ= 15.
(a) P(X > 425) = PXµ
σ>425 450
15 =P(Z > 1.67)
= 1 P(Z 1.67) = 1 .0475 = .9525
(b) z= 1.28 P(Z1.28) .90
z=xµ
σ; 1.28 = x450
15 ;x= 450 + (1.28)(15) = 469.20
3. Correlation and regression by calculator.
(a) r=.245
(b) ˆy= 61.934 + 0.286 x
4. Binomial random variable.
Note : X, # of customers ordering Daily Special, is binomial with n= 20 and π=.25.
(a) P(X < 5) = P(X4) = .4148
(b) P(X= 7) = P(X7) P(X6) = .8982 .7858 = .1124
(c) P(2 < X < 10) = P(X9) P(X2) = .9861 .0913 = .8948
(d) “More than 15 not order Daily Special” means “4 or fewer order Daily Special.”
P(X4) = .4148
Alternatively, let Ybe # of customers not ordering Daily Special. Then,
Yis binomial with n= 20 and π=.75.
P(Y > 15) = 1 P(Y15) = 1 .5852 = .4148
5. Correlation and regression by SPSS.
(a) r2=.190
(b) se= 2.618
(c) ˆy= 28.278 + (1.667)(1.42) = 30.645

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Math 220 : Elementary Statistics Kane Nashimoto Exam 2 Solutions Fall 2006

  1. Probability. E : {selected student is male} F : {selected student prefers morning classes} Note : P (E) = .46 ; P (F ) = .67 ; P (E ∩ F ) =. 29 (a) P (E ∪ F ) = P (E) + P (F ) − P (E ∩ F ) = .46 +. 67 − .29 =. 840 (b) P (F |E) =

P (E ∩ F )

P (E) =^

. 46 =^.^630

(c) P (at least one male) = 1 − P (all female) = 1 − (.54)^3 =. 843 (d) P (E ∩ F ) =. 29 but P (E)P (F ) = (.46)(.67) =. 308 ⇒ Two events are not independent.

  1. Normal random variable. Note : X, heating cost, is normal with μ = 450 and σ = 15.

(a) P (X > 425) = P

X − μ σ

> 425 −^450

= P (Z > − 1 .67)

= 1 − P (Z ≤ − 1 .67) = 1 − .0475 =. 9525

(b) z = 1. 28 ∵ P (Z ≤ 1 .28) ≈. 90 z = x^ − σ μ; 1.28 = x^ − 15 450 ; x = 450 + (1.28)(15) = 469. 20

  1. Correlation and regression by calculator. (a) r =. 245 (b) ˆy = 61.934 + 0. 286 x
  2. Binomial random variable. Note : X, # of customers ordering Daily Special, is binomial with n = 20 and π = .25. (a) P (X < 5) = P (X ≤ 4) =. 4148 (b) P (X = 7) = P (X ≤ 7) − P (X ≤ 6) =. 8982 − .7858 =. 1124 (c) P (2 < X < 10) = P (X ≤ 9) − P (X ≤ 2) =. 9861 − .0913 =. 8948 (d) “More than 15 not order Daily Special” means “4 or fewer order Daily Special.” ⇒ P (X ≤ 4) =. 4148 Alternatively, let Y be # of customers not ordering Daily Special. Then, Y is binomial with n = 20 and π = .75. ⇒ P (Y > 15) = 1 − P (Y ≤ 15) = 1 − .5852 =. 4148
  3. Correlation and regression by SPSS. (a) r^2 =. 190 (b) se = 2. 618 (c) ˆy = 28.278 + (1.667)(1.42) = 30. 645