Answer:
(a) P(0 <= Z <= 2.24) = 0.4927
(b) P(0 <= Z <= 2) = 0.4773
(c) P(-2.60 <= Z <= 0) = 0.4953
(d) P(-2.60 <= Z <= 2.60) = 0.9906
(e) P(Z <= 1.64) = 0.9495
(f) P(-1.75 <= Z) = 0.0047
(g) P(-1.60 <= Z <= 2.00) = 0.9425
(i) P(1.60 <= Z)=0.0548
(j) P(|Z| <= 2.50) = 0.9876
Step-by-step explanation:
(a) P(0 <= Z <= 2.24) = P(Z <= 2.24)- P(Z <= 0)
using the STANDARD NORMAL DISTRIBUTION TABLE
P(0 <= Z <= 2.24) = 0.9927 - 0.5 = 0.4927
(b) P(0 <= Z <= 2) = P(Z <= 2)- P(Z <= 0)
= 0.9773 - 0.5 = 0.4773
(c) P(-2.60 <= Z <= 0) = P(Z <= 0)- P(-2.60)
= 0.5 - 0.0047 = 0.4953
(d) P(-2.60 <= Z <= 2.60) = P(Z <= 2.6)- P(-2.60)
= 0.9953 - 0.0047 = 0.9906
(e) P(Z <= 1.64) = 0.9495
(f) P(-1.75 <= Z) =1 - P(Z < 2.6) = 1 - 0.9953 = 0.0047
(g) P(-1.60 <= Z <= 2.00) = P(Z <= 2.0)- P(-1.60)
= 0.9773- 0.0548 = 0.9425
(i) P(1.60 <= Z)=1 - P(Z < 1.6) = 1 - 0.9452 = 0.0548
(j) P(|Z| <= 2.50) = P(-2.5 < Z <= 2.50)= P(Z <= 2.5)- P(-2.5)
=0.9938 - 0.0062 = 0.9876
