If the change causes all customers to consolidate a number of small orders into… 1 answer below »

Descriptive Statistics
Variable N Mean Median StDev SE Mean
Orders 28 21.32 17.00 13.37 2.53
Variable Min Max Q1 Q3 Orders 5.00 54.00 11.25 28.75
a. = 21.32
b. S = 13.37
c. S2= 178.76
d. If the policy is successful, smaller orders will be eliminated and the mean will
increase.

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  1. If the change causes all customers to consolidate a number of small orders into

large orders, the standard deviation will probably decrease. Otherwise, it is very
difficult to tell how the standard deviation will be affected.
f. The best forecast over the long-term is the mean of 21.32.
3. a. Point estimate:
b. 1-a = .95 Þ Z = 1.96, n = 30,

(5.85%, 15.67%)
c. df = 30-1 = 29, t = 2.045

(5.64%, 15.88%)

  1. We see that the 95% confidence intervals in b and c are not much different because the multipliers 1.96 and 2.045 are nearly the same magnitude.

This explains why a sample of size n = 30 is often taken as the cutoff between
large and small samples.
6. point estimate: 8.1 seats
interval estimate: 8.1 ± 1.96 Þ 6.5 to 9.7 seats
Forecast 8.1 empty seats per flight; very likely the mean number of empty seats will lie between 6.5 and 9.7.
8. df = n -1 = 14 -1 = 13,
one-sided test, a = .05, critical value: t = 1.771
Test statistic:
Since 2.23 > 1.771, reject at the 5% level. The medium-size serving contains an
average of more than 4 ounces of yogurt.
p-value: P(t > 2.23) = .022, strong evidence against

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SOLUTIONS TO ASSIGNED PRACTICE EXERCISES

CHAPTER 2

A REVIEW OF BASIC STATISTICAL CONCEPTS

1. Descriptive Statistics

Variable N Mean Median StDev SE Mean
Orders 28 21.32 17.00 13.37 2.53

Variable Min Max Q1 Q3
Orders 5.00 54.00 11.25 28.75

a. = 21.32
b. S = 13.37
c. S2 = 178.76
d. If the policy is successful, smaller orders will be eliminated and the mean will
increase.

If the change causes all customers to consolidate a number of small orders into
large orders, the standard deviation will probably decrease. Otherwise, it is very
difficult to tell how the standard deviation will be affected.

f. The best forecast over the long-term is the mean of 21.32.

3. a. Point estimate:

b. 1?? = .95 ? Z = 1.96, n = 30,

(5.85%, 15.67%)

c. df = 30?1 = 29, t = 2.045

(5.64%, 15.88%)

We see that the 95% confidence intervals in b and c are not much different because the multipliers 1.96 and 2.045 are nearly the same magnitude.
This explains why a sample of size n = 30 is often taken as the cutoff between
large and small samples.

6. point estimate: 8.1 seats
interval estimate: 8.1 ? 1.96 ? 6.5 to 9.7 seats
Forecast 8.1 empty seats per flight; very likely the mean number of empty seats will lie between 6.5 and 9.7.

8. df = n ?1 = 14 ?1 = 13,
one-sided test, ? = .05, critical value: t = 1.771
Test statistic:

Since 2.23 > 1.771, reject at the 5% level. The medium-size serving contains an
average of more than 4 ounces of yogurt.

p-value: P(t > 2.23) = .022, strong evidence against

12. a.

b. Positive linear relationship

c. r = .95

18. a.

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