course Mth152 ?????????wassignment #018
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20:18:39 **** query problem 13.5.12 percent above 115 IQ, mean 100 std dev 15
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RESPONSE --> z= x- mean /s 115 - 100 = 15 15 / 15 = 1 z = 1 .5 - .341 = .159 15.9 % would be above 115 IQ.
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20:19:22 ** The z-score is measured relative to the mean. The mean is 100, and you need to measure the z score of 115. 115 is 15 units from the mean, which gives you a z-score of 15 / 15 = 1. The table tells you that .339 of the distribution lies between the mean and z = 1. You want the proportion beyond 115. Since half the distribution lies to the right of the mean, and .339 of the distribution lies between the mean and z = 1, we conclude that .5 - .339 = .159 of the distribution lies to the right of z = 1. It follows that .159, or 15.9% of the distribution exceeds an IQ of 115. **
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RESPONSE --> o.k. Why is .339 used instead of .341?
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20:26:11 **** query problem 13.5.20 area between z=-1.74 and z=-1.14
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RESPONSE --> -1.74 = z .373 -1.14 = z .459 1.74 and 1.14 are both negative .459 - .373 = .086 = 8.6%
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20:26:18 ** According to the table the z score for -1.74 is .373 and the z score for -1.14 is .459, meaning that .373 of the distribution lies between the mean and z = -1.73 and .459 of the distribution lies between the mean and z = -1.14. Since -1.74 and -1.14 both lie on the same side of the mean, the region between the mean and -1.74 contains the region between the mean and -1.14. The region lying between z = -1.14 and z = -1.74 is therefore that part of the .459 that doesn't include the .373. The proportion between z = -1.14 and z = -1.74 is therefore .459 - .373 = .086, or 8.6%. **
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RESPONSE --> o.k.
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20:43:52 **** query problem 13.5.30 of 10K bulbs, mean lifetime 600 std dev 50, # between 490 and 720 **** How many bulbs would be expected to last between 490 and 720 hours? **** Describe in detail how you obtained your result.
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RESPONSE --> the mean lifetime is 600 standard deviation is 50 490 - 720 hours z = x- mean / standard deviation 490 - 600 = -110 / 50 = -2.2 area for -2.2 = .487 720 - 600 = 120/50 = 2.4 area for 2.4 = .492 since we want the total of bulbs that would last between 490 and 720 hours we have to add the twoo areas. .487 + .492 = .979 There are a total of 10,000 bulbs so we have to multiply 10,000 x .979 = 9,790
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20:43:58 ** You first calculate the z value for each of the given lifetimes 490 hrs and 720 hrs. You should then sketch a graph of the distribution so you can see how the regions are located within the distribution. Then interpret what the table tells you about the proportion of the distribution within each region and apply the result to the given situation. The details: The displacement from the mean to 490 is 490 - 600 = - 110 (i.e., 490 lies 110 units to the left of the mean). The z value corresponding to 490 hours is therefore z = -110/50 = -2.2. The area of the region between the mean and z = -2.2 is found from the table to be .486. Similarly 720 lies at displacement 720- 600 = 120 from the mean, giving us z = 120/50 = 2.4. The area of the region between the mean and z = 2.4 is shown by the table to be .492. Since one region is on the negative side and the other on the positive side of the mean, the region lying between z = -2.2 and z = 2.4 contains .486 + .492 = .978 of the distribution. Out of 10,000 bulbs we therefore expect that .978 * 10,000 = 9780 of the bulbs will last between 490 and 720 hours. **
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RESPONSE --> o.k.
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21:06:52 **** query problem 13.5.48 A's for > mean + 3/2 s What percent of the students receive A's, and how did you obtain your result?
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RESPONSE --> using the table 1.5 is the z score for .433 since A's are given for z scores that are greater than1.5 1.000 - .433 = .567 .567 = 6.7 %
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21:07:59 ** A's are given for z scores greater than 1.5. The area between mean and z = 1.5 is given by the table as .433. To the right of z = 1.5, corresponding to the A's, we have .500 - .433 = .067 or 6.7% of the total area. So we expect that 6.7% of the group will receive A's. **
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RESPONSE --> o.k. why was .500 used instead of 1.00?
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21:08:11 GENERAL ADVICE: To solve problems of the type covered in this section it is a good idea to follow a strategy something like the following: 1. Find the z-score(s) corresponding to the given values. 2. Look up the corresponding numbers on the table. 3. Sketch a graph of the normal distribution representing what the numbers in the table tell you. Be sure you understand that the table tells you the proportion of the distribution lying between the mean and the given z value. 4. Decide what region of the graph corresponds to the result you are trying to find. 5. Find the proportion of the total area lying within this region. 6. If necessary apply this proportion to the given numbers to get your final result. See how this procedure is applied in the given solutions. Then you should probably rework the section, being sure your answers agree with those given in the back of the text, and send me questions about anything you aren? sure you understand.
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RESPONSE --> o.k.
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