3. Find the data female and male life expectancy for the 13 richest and 14 poorest countries on earth.
Country ID |
Country Name |
Female LE |
Male LE |
1 |
Japan |
86.8 |
80.5 |
2 |
Switzerland |
85.3 |
81.3 |
3 |
Singapore |
86.1 |
80 |
4 |
Australia |
84.8 |
80.9 |
5 |
Spain |
85.5 |
80.1 |
6 |
Iceland |
84.1 |
81.2 |
7 |
Italy |
84.8 |
80.5 |
8 |
Israel |
84.3 |
80.6 |
9 |
Sweden |
84 |
80.7 |
10 |
France |
85.4 |
79.4 |
11 |
south Korea |
85.5 |
78.8 |
12 |
Canada |
84.1 |
80.2 |
13 |
Luxembourg |
84 |
79.8 |
170 |
Malawi |
59.9 |
56.7 |
171 |
Mali |
58.3 |
58.2 |
172 |
Guinea |
60 |
56.6 |
173 |
Mozambique |
59.4 |
55.7 |
174 |
South Sudan |
58.6 |
56.1 |
175 |
Cameroon |
58.6 |
55.9 |
176 |
Somalia |
56.6 |
53.5 |
177 |
Nigeria |
55.6 |
53.4 |
178 |
Lesotho |
55.4 |
51.7 |
179 |
Cote d'Ivoire |
54.4 |
52.3 |
180 |
Chad |
54.5 |
51.7 |
181 |
Central African Republic |
54.1 |
50.9 |
182 |
Angola |
54 |
50.9 |
183 |
Sierra Leon |
50.8 |
49.3 |
Test whether there is a difference of variances between male life expectancy of richest and poorest countries.
Test whether there is a difference of variances between female life expectancy of richest and poorest countries.
In: Math
Among a simple random sample of 322 American adults who do not have a four-year college degree and are not currently enrolled in school, 145 said they decided not to go to college because they could not afford school.
1. Calculate a 99% confidence interval for the proportion of Americans who decide to not go to college because they cannot afford it, and interpret the interval in context. Round to 4 decimal places.
( , )
2. Suppose we wanted the margin of error for the 99% confidence level to be about 3.25%. What is the smallest sample size we could take to achieve this? Note: For consistency's sake, round your z* value to 3 decimal places before calculating the necessary sample size.
Choose n =
In: Math
Given the question:
"Researchers found that 25% of the beech trees in east central Europe had been damaged by fungi. Consider a sample of 20 beech trees from this area.
How many of the sampled trees would you expect to be damaged by fungi?"
I was asked, "The question as asked is misleading, why? Nevertheless, give a numerical answer."
I don't see how this question is misleading. All I can think of it asking for is expected value, which would be µ = (0.25)(20) = 5. So my question is not what the expected value is, my question is how is the question misleading, what am I missing here?
In: Math
In: Math
Consider the following gasoline sales time series. If needed, round your answers to two-decimal digits.
|
In: Math
4. In a survey sponsored by the Lindt chocolate company, 1708 women were surveyed and 85% of them said that chocolate made them happier. (a) Is there anything potentially wrong with this survey? (b) Of the 1708 women surveyed, what is the number of them who said that chocolate made them happier? (c) Use Excel to construct a 98% confidence interval estimate of the percentage of women who say that chocolate makes them happier. Insert a screenshot, write down the confidence interval and write a brief statement interpreting the result. 3 (d) Use Excel to test the claim that when asked, more than 80% of women say that chocolate makes them happier. Use a 0.02 significance level. (i.e. complete steps (a) to (e) similar to question 3) (e) Does your result from (d) contradict your result from (c)? Explain
In: Math
The U-Plant’um Nursery must determine if there is a difference in the growth rate of saplings that have been treated with four different chemical formulas. The resulting growth rates over a given period are shown here. Does a difference appear to exist in the growth factor of the formulas? Set alpha = 0.01.
FORMULA
10 8 5 7
12 15 17 14
17 16 15 15
In: Math
5. Listed in the table below are the robbery and aggravated assault rates (occurrences per 100,000) for the 12 most populated U.S. cities in 2006: City Robbery (x) Aggravated Assault (y) New York 288 330 Los Angeles 370 377 Chicago 555 610 Houston 548 562 Phoenix 288 398 Philadelphia 749 720 Las Vegas 409 508 San Antonio 180 389 San Diego 171 301 Dallas 554 584 San Jose 112 248 Honolulu 105 169 a. Calculate the standard error of the estimate. b. Estimate the strength of the linear relationship between x and y.
In: Math
A 99% CI on the difference between means will be (longer than/wider than/the same length as/shorter than/narrower than )a 95% CI on the difference between means.
In semiconductor manufacturing, wet chemical etching is often
used to remove silicon from the backs of wafers prior to
metalization. The etch rate is an important characteristic in this
process and known to follow a normal distribution. Two different
etching solutions have been compared, using two random samples of
10 wafers for each solution. Assume the variances are equal. The
etch rates are as follows (in mils per minute):
Solution 1 |
Solution 2 |
|||
9.8 |
10.2 |
10.6 |
10.4 |
|
9.4 |
10.3 |
10.6 |
10.2 |
|
9.3 |
10.0 |
10.7 |
10.7 |
|
9.6 |
10.3 |
10.4 |
10.4 |
|
10.2 |
10.1 |
10.5 |
10.3 |
(a) Calculate the sample mean for solution 1: x¯1= Round
your answer to two decimal places (e.g. 98.76).
(b) Calculate the sample standard deviation for solution 1:
s1 = Round your answer to three
decimal places (e.g. 98.765).
(c) Calculate the sample mean for solution 2: x¯2= Round
your answer to two decimal places (e.g. 98.76).
(d) Calculate the sample standard deviation for solution 2:
s1 = Round your answer to three
decimal places
(e) Test the hypothesis H0:μ1=μ2 vs H1:μ1≠μ2.
Calculate t0 = Round your answer to
two decimal places (e.g. 98.76).
(f) Do the data support the claim that the mean etch rate is
different for the two solutions? Use α=0.05.
yesno
(g) Calculate a 95% two-sided confidence interval on the difference
in mean etch rate.
(Calculate using the following order: x¯1-x¯2)
( ≤ μ1-μ2 ≤ ) Round your answers to
three decimal places (e.g. 98.765).
In: Math
suppose we take a die with 3 on three sides 2 on two sides and 1 on one side, roll it n times and let Xi be the number of times side i appeared find the conditional distribution P(X2=k|X3=m)
In: Math
1. Consider the relationship between the number of bids an item on eBay received and the item's selling price. The following is a sample of 55 items sold through an auction.
Price in Dollars | 2222 | 2626 | 2727 | 3636 | 4545 |
---|---|---|---|---|---|
Number of Bids | 11 | 44 | 55 | 55 | 77 |
Step 1 of 5: Calculate the sum of squared errors (SSE). Use the values b0= −1.9336 and b1= 0.2030 for the calculations. Round your answer to three decimal places.
Step 2 of 5: Calculate the estimated variance of errors, s2e. Round your answer to three decimal places.
Step 3 of 5: Calculate the estimated variance of slope, s2b1. Round your answer to three decimal places.
Step 4 of 5: Construct the 80% confidence interval for the slope. Round your answers to three decimal places.
Lower endpoint:
Upper endpoint:
Step 5 of 5: Construct the 98% confidence interval for the slope. Round your answers to three decimal places.
Lower endpoint:
Upper endpoint:
In: Math
Customer | Type of Customer | Items | Net Sales | Method of Payment | Gender | Marital Status | Age |
1 | Regular | 1 | 49.5 | Discover | Male | Married | 22 |
2 | Promotional | 1 | 112.4 | Proprietary Card | Female | Married | 26 |
3 | Regular | 1 | 32.5 | Proprietary Card | Female | Married | 22 |
4 | Promotional | 5 | 110.4 | Proprietary Card | Female | Married | 18 |
5 | Regular | 2 | 64 | MasterCard | Female | Married | 24 |
6 | Regular | 1 | 54.5 | MasterCard | Female | Married | 34 |
7 | Promotional | 2 | 88 | Proprietary Card | Female | Married | 20 |
8 | Regular | 1 | 32.5 | Visa | Female | Married | 30 |
9 | Promotional | 2 | 66.52 | Proprietary Card | Female | Married | 36 |
10 | Regular | 1 | 54.5 | Proprietary Card | Female | Married | 26 |
11 | Regular | 1 | 39.5 | Proprietary Card | Female | Married | 38 |
12 | Promotional | 1 | 41.6 | Proprietary Card | Female | Married | 30 |
13 | Promotional | 9 | 170.4 | Visa | Female | Married | 30 |
14 | Promotional | 2 | 74.5 | Visa | Female | Married | 36 |
15 | Regular | 1 | 59.5 | Visa | Male | Single | 44 |
16 | Promotional | 2 | 81.4 | Proprietary Card | Male | Single | 26 |
17 | Promotional | 3 | 104 | Proprietary Card | Female | Single | 32 |
18 | Regular | 3 | 64.5 | Discover | Female | Married | 30 |
19 | Promotional | 2 | 48.5 | MasterCard | Female | Married | 22 |
20 | Promotional | 6 | 54.8 | Proprietary Card | Female | Married | 46 |
21 | Promotional | 1 | 41.6 | Proprietary Card | Female | Single | 18 |
22 | Promotional | 4 | 80.82 | Proprietary Card | Female | Married | 28 |
23 | Promotional | 7 | 276 | American Express | Female | Married | 40 |
24 | Regular | 2 | 84 | Proprietary Card | Female | Married | 32 |
25 | Promotional | 2 | 49.5 | Visa | Male | Married | 38 |
26 | Promotional | 1 | 40.02 | Proprietary Card | Female | Married | 50 |
27 | Regular | 1 | 54.5 | Proprietary Card | Female | Married | 44 |
28 | Promotional | 5 | 202.8 | Proprietary Card | Female | Single | 32 |
29 | Promotional | 3 | 81.2 | Proprietary Card | Female | Married | 22 |
30 | Promotional | 1 | 28 | Proprietary Card | Female | Married | 60 |
31 | Promotional | 2 | 73.2 | MasterCard | Female | Married | 18 |
32 | Regular | 1 | 85 | Proprietary Card | Female | Married | 42 |
33 | Promotional | 3 | 73.2 | Proprietary Card | Female | Married | 34 |
34 | Regular | 1 | 50 | Proprietary Card | Female | Married | 24 |
35 | Promotional | 5 | 115.5 | MasterCard | Female | Married | 46 |
36 | Regular | 1 | 39.5 | MasterCard | Male | Single | 26 |
37 | Regular | 2 | 112.5 | Visa | Female | Single | 32 |
38 | Promotional | 6 | 127.5 | Proprietary Card | Female | Married | 40 |
39 | Promotional | 5 | 23.23 | Proprietary Card | Female | Married | 34 |
40 | Regular | 2 | 62.5 | Proprietary Card | Female | Married | 48 |
41 | Promotional | 13 | 208.8 | Proprietary Card | Female | Married | 32 |
42 | Promotional | 4 | 29.5 | Visa | Female | Married | 36 |
43 | Regular | 2 | 133.5 | Proprietary Card | Female | Married | 38 |
44 | Promotional | 1 | 72.4 | Proprietary Card | Female | Married | 44 |
45 | Promotional | 2 | 33.8 | Proprietary Card | Female | Married | 28 |
46 | Promotional | 2 | 49.6 | Proprietary Card | Female | Married | 50 |
47 | Regular | 1 | 35 | MasterCard | Female | Married | 36 |
48 | Promotional | 3 | 73.64 | Proprietary Card | Female | Married | 20 |
49 | Promotional | 1 | 24.82 | Proprietary Card | Female | Married | 22 |
50 | Promotional | 9 | 155.2 | MasterCard | Female | Married | 36 |
51 | Promotional | 6 | 186.62 | Proprietary Card | Female | Married | 28 |
52 | Promotional | 5 | 128.8 | Proprietary Card | Male | Married | 58 |
53 | Regular | 1 | 68 | Discover | Female | Single | 68 |
54 | Regular | 2 | 84 | Visa | Female | Single | 84 |
55 | Regular | 2 | 59.5 | MasterCard | Female | Married | 22 |
56 | Promotional | 3 | 151.6 | Proprietary Card | Female | Married | 28 |
57 | Promotional | 6 | 133.1 | Proprietary Card | Female | Married | 44 |
58 | Promotional | 2 | 90.4 | Proprietary Card | Female | Married | 38 |
59 | Promotional | 4 | 75.2 | MasterCard | Female | Married | 36 |
60 | Promotional | 4 | 123 | Proprietary Card | Female | Single | 40 |
61 | Promotional | 1 | 118.8 | Proprietary Card | Female | Married | 36 |
62 | Promotional | 3 | 69.91 | Proprietary Card | Female | Single | 20 |
63 | Promotional | 5 | 63.6 | Proprietary Card | Female | Married | 44 |
64 | Promotional | 1 | 41.6 | Proprietary Card | Female | Single | 32 |
65 | Promotional | 2 | 59.5 | Proprietary Card | Female | Married | 38 |
66 | Promotional | 1 | 49.6 | Proprietary Card | Female | Married | 52 |
67 | Promotional | 2 | 69.5 | Proprietary Card | Female | Married | 24 |
68 | Promotional | 5 | 156.8 | Proprietary Card | Female | Married | 18 |
69 | Promotional | 2 | 57.2 | Proprietary Card | Male | Married | 36 |
70 | Promotional | 8 | 105.05 | Proprietary Card | Female | Married | 44 |
71 | Promotional | 5 | 165.32 | Proprietary Card | Female | Married | 20 |
72 | Promotional | 4 | 68 | MasterCard | Female | Married | 22 |
73 | Regular | 1 | 79 | Proprietary Card | Female | Single | 54 |
74 | Promotional | 2 | 56.5 | Proprietary Card | Female | Married | 22 |
75 | Promotional | 2 | 55.22 | Proprietary Card | Female | Married | 64 |
76 | Promotional | 4 | 94.74 | Proprietary Card | Female | Married | 52 |
77 | Regular | 2 | 49 | Proprietary Card | Female | Married | 32 |
78 | Promotional | 4 | 121.14 | Proprietary Card | Female | Married | 18 |
79 | Promotional | 3 | 96.8 | Proprietary Card | Female | Married | 28 |
80 | Regular | 2 | 99 | Discover | Female | Married | 44 |
81 | Promotional | 2 | 88 | MasterCard | Female | Married | 58 |
82 | Promotional | 6 | 63.2 | Proprietary Card | Female | Single | 20 |
83 | Promotional | 4 | 68.5 | Visa | Female | Married | 26 |
84 | Promotional | 3 | 56 | Proprietary Card | Female | Married | 34 |
85 | Regular | 2 | 47.5 | Visa | Female | Married | 34 |
86 | Promotional | 1 | 30.8 | Proprietary Card | Female | Married | 52 |
87 | Regular | 6 | 154 | MasterCard | Female | Single | 38 |
88 | Regular | 4 | 117 | Proprietary Card | Female | Married | 26 |
89 | Promotional | 1 | 41.6 | Proprietary Card | Female | Single | 50 |
90 | Promotional | 6 | 67.6 | Proprietary Card | Female | Married | 32 |
91 | Promotional | 4 | 105.2 | Proprietary Card | Female | Married | 44 |
92 | Promotional | 1 | 32.42 | Proprietary Card | Female | Married | 44 |
93 | Regular | 5 | 169.75 | Proprietary Card | Female | Married | 62 |
94 | Promotional | 17 | 239.5 | Proprietary Card | Female | Married | 20 |
95 | Regular | 3 | 76 | American Express | Female | Married | 36 |
96 | Regular | 1 | 49.5 | MasterCard | Female | Married | 34 |
97 | Promotional | 9 | 263 | Proprietary Card | Female | Married | 20 |
98 | Promotional | 10 | 297.59 | Proprietary Card | Female | Married | 42 |
99 | Promotional | 2 | 57.6 | Proprietary Card | Female | Married | 20 |
100 | Promotional | 1 | 38.44 | Proprietary Card | Female | Married | 34 |
a) Using the empirical rule, 95% of female promotional customer ages should be between what two values? Either show work or explain how your answer was calculated.
b)Using the empirical rule, 68% of items purchased should be between what two values? Either show work or explain how your answer was calculated.
In: Math
36 |
16 |
61 |
97 |
27 |
37 |
64 |
59 |
91 |
81 |
86 |
39 |
56 |
85 |
26 |
36 |
51 |
18 |
68 |
69 |
78 |
61 |
49 |
29 |
82 |
In: Math
Consider the following experiment: we roll a fair die twice. The two rolls are independent events. Let’s call M the number of dots in the first roll and N the number of dots in the second roll.
(a) What is the probability that both M and N are even?
(b) What is the probability that M + N is even?
(c) What is the probability that M + N = 5?
(d) We know that M + N = 5. What is the probability that M is an odd number?
(e) We know that M is an odd number. What is the probability that M + N = 5?
In: Math
A company maintains three offices in a certain region, each staffed by two employees. Information concerning yearly salaries (1000s of dollars) is as follows:
Office | 1 | 1 | 2 | 2 | 3 | 3 |
Employee | 1 | 2 | 3 | 4 | 5 | 6 |
Salary | 24.7 | 28.6 | 25.2 | 28.6 | 20.8 | 24.7 |
(a) Suppose two of these employees are randomly selected from among the six (without replacement). Determine the sampling distribution of the sample mean salary X. (Enter your answers for p(x) as fractions.)
x | 22.75 | 24.70 | 24.95 | 26.65 | 28.60 | ||||||
p(x) |
|
|
(b) Suppose one of the three offices is randomly selected. Let
X1 and X2 denote the
salaries of the two employees. Determine the sampling distribution
of X. (Enter your answers as fractions.)
x | 22.75 | 26.65 | 26.90 |
p(x) |
(c) How does E(X) from parts (a) and (b)
compare to the population mean salary μ?
E(X) from part (a) is _______ μ, and E(X) from part (b) is _______ μ.
In: Math