Suppose we use the mean of a random sample of size n = 100 to estimate the mean of a population with σ = 30 . Use the central limit theorem to compute the probability that the error is less than 6. Express your answer as a decimal using 4 decimal places. Give the exact value on the chart. Do not round your answer..... TABLE II Normal-Curve AreasZ.00.01.02.03.04.05.06.07.08.090.0.0000.0040.00800.1.0398.0438.04780.2.0793.08320.3.1179.12170.4.1554.15910.5.1915.1950.0120 .0160.0517 .0557.0871 .0910. .0948.1255 .1293 .1331.1628 .1664 .1700.1985 .2019 .2054.0199 .0239 .0279 .0319 .0359.0596 .0636 .0675 .0714 .0753.0987 .1026 .1064 .1103 .1141.1368 .1406 .1443 .1480 .1517.1736 .1772 .1808 .1844 .1879.2088 .2123 .2157 .2190 .22240.6.2257.2291.2324.23570.72580.2611.2642.2673.2389 .2422.2704 .27340.8.2881.2910.2939.2967.2995.30230.9.3159 .3186 .3212.3238.3264.32891.0.3413.3438.3461.3485.3508.3531.2454 .2486 .2517 .2549.2764 .2794 .2823 .2852.3051 .3078 .3106 .3133.3315 .3340 .3365 .3389.3554 .3577 .3599 .36211.1.3643.3665.3686.3708.3729.3749.3770 .3790.3810 .38301.2.3849.3869.3888.3907.39251.3.4032.4049.4066.4082.3944 .3962 .3980.4099 .4115 .4131.3997 .40151.4.4192 .4207.4222.4236.4147 .4162 .4177.4251. .4265 .4279 .4292 .4306.43191.5.4332.4345.4357.4370.4382 .4394 .4406 .4418 .4429.44411.6.4452 .4463.4474.44841.7.4554 .4564.4573 .4582.4495 .4505.4591 .45991.8.4641 .4649.4656.46641.9.4713 .4719 .47262.0.4772.4732.4778 .4783 .4788.4515 .4525 .4535.4608 .4616 .4625 .4633.4671 .4678 .4686 .4693 .4699 .4706.4738 .4744 .4750 .4756.4793 .4798 .4803 .4808.4545.4761 .4767.4812 .48172.42.5222222.1.4821 .4826 .4830 .4834 .4838 .4842.4861 .4864 .4868 .4871.4878.48752.3.4893.4896 .4898.4901.4904.4906.4846 .4850 .4854 .4857.4881 .4884 .4887 .4890.4909.4911 .4913.4916.4918 .4920 .4922.4925.4927.4929.4931.4938.4940.4941.4943 .4945.4946 .4948.4932 .4934.4949.4936.4951 .49522.6.4953 .4955.4956.4957.4959.4960.49612.7.4965 .4966.4967.4968.4969.4970.49712.8.4974.4975 .4976 .4977.4977.4978.4962 .4963 .4964.4972 .4973 .4974.4979 .4979 .4980 .49812.9.4981 4982 .4982.4983.4984.4984.4985.4985.4986 .49863.0.4987.49874987.4988.4988.4989.4989 .4989.4990.4990Also, for z=4.0, 5.0, and 6.0, the areas are 0.49997, 0.4999997, and 0.499999999.

The central limit theorem states that the approximation of the sample means approximates the normal…

Answered: Suppose we use the mean of a random…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 31PPS

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Suppose we use the mean of a random sample of size n = 100 to estimate the mean of a population with σ = 30 . Use the central limit theorem to compute the probability that the error is less than 6. Express your answer as a decimal using 4 decimal places. Give the exact value on the chart. Do not round your answer.....

TABLE II Normal-Curve Areas
Z
.00
.01
.02
.03
.04
.05
.06
.07
.08
.09
0.0
.0000
.0040
.0080
0.1
.0398
.0438
.0478
0.2
.0793
.0832
0.3
.1179
.1217
0.4
.1554
.1591
0.5
.1915
.1950
.0120 .0160
.0517 .0557
.0871 .0910. .0948
.1255 .1293 .1331
.1628 .1664 .1700
.1985 .2019 .2054
.0199 .0239 .0279 .0319 .0359
.0596 .0636 .0675 .0714 .0753
.0987 .1026 .1064 .1103 .1141
.1368 .1406 .1443 .1480 .1517
.1736 .1772 .1808 .1844 .1879
.2088 .2123 .2157 .2190 .2224
0.6
.2257
.2291
.2324
.2357
0.7
2580
.2611
.2642
.2673
.2389 .2422
.2704 .2734
0.8
.2881
.2910
.2939
.2967
.2995
.3023
0.9
.3159 .3186 .3212
.3238
.3264
.3289
1.0
.3413
.3438
.3461
.3485
.3508
.3531
.2454 .2486 .2517 .2549
.2764 .2794 .2823 .2852
.3051 .3078 .3106 .3133
.3315 .3340 .3365 .3389
.3554 .3577 .3599 .3621
1.1
.3643
.3665
.3686
.3708
.3729
.3749
.3770 .3790
.3810 .3830
1.2
.3849
.3869
.3888
.3907
.3925
1.3
.4032
.4049
.4066
.4082
.3944 .3962 .3980
.4099 .4115 .4131
.3997 .4015
1.4
.4192 .4207
.4222
.4236
.4147 .4162 .4177
.4251. .4265 .4279 .4292 .4306
.4319
1.5
.4332
.4345
.4357
.4370
.4382 .4394 .4406 .4418 .4429
.4441
1.6
.4452 .4463
.4474
.4484
1.7
.4554 .4564
.4573 .4582
.4495 .4505
.4591 .4599
1.8
.4641 .4649
.4656
.4664
1.9
.4713 .4719 .4726
2.0
.4772
.4732
.4778 .4783 .4788
.4515 .4525 .4535
.4608 .4616 .4625 .4633
.4671 .4678 .4686 .4693 .4699 .4706
.4738 .4744 .4750 .4756
.4793 .4798 .4803 .4808
.4545
.4761 .4767
.4812 .4817
2.4
2.5
22222
2.1
.4821 .4826 .4830 .4834 .4838 .4842
.4861 .4864 .4868 .4871
.4878
.4875
2.3
.4893
.4896 .4898
.4901
.4904
.4906
.4846 .4850 .4854 .4857
.4881 .4884 .4887 .4890
.4909
.4911 .4913
.4916
.4918 .4920 .4922
.4925
.4927
.4929
.4931
.4938
.4940
.4941
.4943 .4945
.4946 .4948
.4932 .4934
.4949
.4936
.4951 .4952
2.6
.4953 .4955
.4956
.4957
.4959
.4960
.4961
2.7
.4965 .4966
.4967
.4968
.4969
.4970
.4971
2.8
.4974
.4975 .4976 .4977
.4977
.4978
.4962 .4963 .4964
.4972 .4973 .4974
.4979 .4979 .4980 .4981
2.9
.4981 4982 .4982
.4983
.4984
.4984
.4985
.4985
.4986 .4986
3.0
.4987
.4987
4987
.4988
.4988
.4989
.4989 .4989
.4990
.4990
Also, for z=4.0, 5.0, and 6.0, the areas are 0.49997, 0.4999997, and 0.499999999.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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