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DedPeter [7]
3 years ago
10

A statistics practitioner determined that the mean and standard deviation of a data set were 120 and 30, is respectively. What c

an you say about the proportions of observations that lie between each of the follow- ing intervals?
a. 90 and 150
b. 60 and 180
c. 30 and 210
Mathematics
1 answer:
BartSMP [9]3 years ago
4 0

Answer:

a) 68% of the observations lie between 90 and 150.

b) 95% of the observations lie between 60 and 180.

c) 99.7% of the observations lie between 30 and 210.

Step-by-step explanation:

The Empirical Rule states that, for a normally distributed random variable:

68% of the measures are within 1 standard deviation of the mean.

95% of the measures are within 2 standard deviation of the mean.

99.7% of the measures are within 3 standard deviations of the mean.

In this problem, we have that:

Standard deviation = 120

Mean = 30

a. 90 and 150

This is within 1 standard deviation of the mean.

By the Empirical Rule, 68% of the observations lie between 90 and 150.

b. 60 and 180

This is within 2 standard deviations of the mean.

By the Empirical Rule, 95% of the observations lie between 60 and 180.

c. 30 and 210

This is within 3 standard deviations of the mean.

By the Empirical Rule, 99.7% of the observations lie between 30 and 210.

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Let Z be a standard normal random variable and calculate the following probabilities, drawing pictures wherever appropriate. (Ro
puteri [66]

Answer:

(a) P(0 ≤ Z ≤ 2.87)=0.498

(b) P(0 ≤ Z ≤ 2)=0.477

(c) P(−2.20 ≤ Z ≤ 0)=0.486

(d) P(−2.20 ≤ Z ≤ 2.20)=0.972

(e) P(Z ≤ 1.01)=0.844

(f) P(−1.95 ≤ Z)=0.974

(g) P(−1.20 ≤ Z ≤ 2.00)=0.862

(h) P(1.01 ≤ Z ≤ 2.50)=0.150

(i) P(1.20 ≤ Z)=0.115

(j) P(|Z| ≤ 2.50)=0.988

Step-by-step explanation:

(a) P(0 ≤ Z ≤ 2.87)

In this case, this is equal to the difference between P(z<2.87) and P(z<0). The last term is substracting because is the area under the curve that is included in P(z<2.87) but does not correspond because the other condition is that z>0.

P(0 \leq z \leq 2.87)= P(z

(b) P(0 ≤ Z ≤ 2)

This is the same case as point a.

P(0 \leq z \leq 2)= P(z

(c) P(−2.20 ≤ Z ≤ 0)

This is the same case as point a.

P(-2.2 \leq z \leq 0)= P(z

(d) P(−2.20 ≤ Z ≤ 2.20)

This is the same case as point a.

P(-2.2 \leq z \leq 2.2)= P(z

(e) P(Z ≤ 1.01)

This can be calculated simply as the area under the curve for z from -infinity to z=1.01.

P(z\leq1.01)=0.844

(f) P(−1.95 ≤ Z)

This is best expressed as P(z≥-1.95), and is calculated as the area under the curve that goes from z=-1.95 to infininity.

It also can be calculated, thanks to the symmetry in z=0 of the standard normal distribution, as P(z≥-1.95)=P(z≤1.95).

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(g) P(−1.20 ≤ Z ≤ 2.00)

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P(-1.20 \leq z \leq 2.00)= P(z

(h) P(1.01 ≤ Z ≤ 2.50)

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