11.12: Solutions
- Page ID
- 261853
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N
(10, 108)(10, 108)" role="presentation" style="position: relative;">
- Χ = amount of change students carry
- Χ ~ E(0.88, 0.88)
- x¯x¯" role="presentation" style="position: relative;">
x¯x¯x¯ = average amount of change carried by a sample of 25 sstudents. - x¯x¯" role="presentation" style="position: relative;">
x¯x¯x¯ ~ N(0.88, 0.176) - 0.0819
- 0.4276
- The distributions are different. Part a is exponential and part b is normal.
- length of time for an individual to complete IRS form 1040, in hours.
- mean length of time for a sample of 36 taxpayers to complete IRS form 1040, in hours.
- N(10.53, 13)(10.53, 13)" role="presentation" style="position: relative;">
(10.53, 13)(10.53, 13)(10.53, 13) - Yes. I would be surprised, because the probability is almost 0.
- No. I would not be totally surprised because the probability is 0.2312
- the length of a song, in minutes, in the collection
- U(2, 3.5)
- the average length, in minutes, of the songs from a sample of five albums from the collection
- N(2.75, 0.0660)
- 2.71 minutes
- 0.09 minutes
- True. The mean of a sampling distribution of the means is approximately the mean of the data distribution.
- True. According to the Central Limit Theorem, the larger the sample, the closer the sampling distribution of the means becomes normal.
- False. The standard deviation of the sample distribution of the means will decrease as the sample size increases; however, the standard deviation of the sample distribution of the means will not equal the standard deviation of X.
- X = the yearly income of someone in a developing country
- the average salary from samples of 1,000 residents of a developing country
- X¯X¯" role="presentation" style="position: relative;">
X¯¯¯X¯X¯ ∼ N(2000, 80001000)(2000, 80001000)" role="presentation" style="position: relative;">(2000, 80001000√)(2000, 80001000)(2000, 80001000) - Very wide differences in data values can have averages smaller than standard deviations.
- The distribution of the sample mean will have higher probabilities closer to the population mean.
P(2000 < x¯x¯" role="presentation" style="position: relative;">x¯x¯x¯ < 2100) = 0.1537
P(2100 < x¯x¯" role="presentation" style="position: relative;">x¯x¯x¯ < 2200) = 0.1317
- the total length of time for nine criminal trials
- N(189, 21)
- 0.0432
- 162.09; ninety percent of the total nine trials of this type will last 162 days or more.
- X = the salary of one elementary school teacher in the district
- X ~ N(44,000, 6,500)
- ΣX ~ sum of the salaries of ten elementary school teachers in the sample
- ΣX ~ N(44000, 20554.80)
- 0.9742
- $52,330.09
- 466,342.04
- Sampling 70 teachers instead of ten would cause the distribution to be more spread out. It would be a more symmetrical normal curve.
- If every teacher received a $3,000 raise, the distribution of X would shift to the right by $3,000. In other words, it would have a mean of $47,000.
- X = the closing stock prices for U.S. semiconductor manufacturers
- i. $20.71; ii. $17.31; iii. 35
- Exponential distribution, Χ ~ Exp(120.71)(120.71)" role="presentation" style="position: relative;">
(120.71)(120.71)(120.71) - Answers will vary.
- i. $20.71; ii. $11.14
- Answers will vary.
- Answers will vary.
- Answers will vary.
- N(20.71, 17.315)(20.71, 17.315)" role="presentation" style="position: relative;">
(20.71, 17.315√)(20.71, 17.315)(20.71, 17.315)
- Answers may vary.
- X¯X¯" role="presentation" style="position: relative;">
X¯¯¯X¯X¯ ~ N(60, 925)(60, 925)" role="presentation" style="position: relative;">(60, 925√)(60, 925)(60, 925) - 0.5000
- 59.06
- 0.8536
- 0.1333
- N(1500, 45)
- 1530.35
- 0.6877
- We have μ = 17, σ = 0.8, x¯x¯" role="presentation" style="position: relative;">
x¯x¯x¯ = 16.7, and n = 30. To calculate the probability, we usenormalcdf(lower, upper, μ, σnσn" role="presentation" style="position: relative;">σn√σnσn ) =normalcdf(E–99,16.7,17,0.830)(E–99,16.7,17,0.830)" role="presentation" style="position: relative;">(E–99,16.7,17,0.830√)(E–99,16.7,17,0.830)(E–99,16.7,17,0.830) = 0.0200. - If the process is working properly, then the probability that a sample of 30 batteries would have at most 16.7 lifetime hours is only 2%. Therefore, the class was justified to question the claim.
- For the sample, we have n = 100, x¯x¯" role="presentation" style="position: relative;">
x¯x¯x¯ = 0.862, s = 0.05 - Σx¯Σx¯" role="presentation" style="position: relative;">
Σx¯Σx¯Σx¯ = 85.65, Σs = 5.18 normalcdf(396.9,E99,(465)(0.8565),(0.05)(465465" role="presentation" style="position: relative;">465−−−√465465 )) ≈ 1- Since the probability of a sample of size 465 having at least a mean sum of 396.9 is appproximately 1, we can conclude that Mars is correctly labeling their M&M packages.
Use normalcdf(E–99,1.1,1,170)(E–99,1.1,1,170)" role="presentation" style="position: relative;">
We assume that the weights of coins are normally distributed in the population. Since we have normalcdf(5.111,5.291,5.201,0.065280)(5.111,5.291,5.201,0.065280)" role="presentation" style="position: relative;">

