Question Five The management of a supermarket wants to adopt a new promotional policy of giving free gift to every customer who spends more than a certain amount per visit at this supermarket. The expectation of the management is that after this promotional policy is advertised, the expenditure for all customers at this supermarket will be normally distributed with mean 400 £ and a variance of 900 £?. 1) If the management wants to give free gifts to at most 10% of the customers, what should the amount be above which a customer would receive a free gift? 2) In a sample of 100 customers, what are the number of customers whose expenditure is between 420 £ and 485 £? 3) What is a probability of selecting a customer whose expenditure is differ than the population mean expenditure by at most 50 £? 4) In a sample of 49 customers, what are the number of customers whose mean expenditure is at least 410 £? 5) What is the probability that the expenditure of the first customer exceeds the expenditure of the second customer by at least 20 £?
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
![Question Five
The management of a supermarket wants to adopt a new promotional policy of
giving free gift to every customer who spends more than a certain amount per visit
at this supermarket. The expectation of the management is that after this
promotional policy is advertised, the expenditure for all customers at this
supermarket will be normally distributed with mean 400 £ and a variance of 900
£?.
1) If the management wants to give free gifts to at most 10% of the customers,
what should the amount be above which a customer would receive a free
gift?
2) In a sample of 100 customers, what are the number of customers whose
expenditure is between 420 £ and 485 £?
3) What is a probability of selecting a customer whose expenditure is differ than
the population mean expenditure by at most 50 £?
4) In a sample of 49 customers, what are the number of customers whose
mean expenditure is at least 410 £?
5) What is the probability that the expenditure of the first customer exceeds the
expenditure of the second customer by at least 20 £?](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fa7e25249-a446-45b2-8ab3-d84efc7ba7c0%2Ffc4ef7a2-56dd-45e9-9627-3ff2f5bff4a3%2Fs8e1fx_processed.jpeg&w=3840&q=75)
![TABLE D.1
AREAS UNDER THE STANDARDIZED NORMAL DISTRIBUTION
Example
Pr(0sZ<1.96)-0.4750
Pr(Z z1.96) -0.5-0.4750 -0.025
0.4750
1.96
00
.01
.02
.03
.04
.05
.06
.07
.08
.09
0.0
.0000
.0398
.0040
.0080
.0120
.0517
.0160
0199
.0239
.0279
.0675
.0319
.0359
0.1
.0438
.0478
.0596
.0987
.1368
.1736
.0636
.1026
.1406
.1772
2123
.0557
.0714
.0753
0.2
.0793
.0832
.0871
.1255
.0910
.0948
.1331
1700
.1064
.1103
.1480
.1844
2190
.1141
0.3
.1179
.1554
.1915
.1217
1293
.1443
.1808
2157
.1517
0.4
.1591
.1628
.1664
.1879
2224
0.5
.1950
.1985
2019
2054
2088
0.6
2257
2580
2291
2324
2642
2357
2389
2422
2454
2486
2517
2549
2852
0.7
2611
.2673
2704
2734
2764
2794
2823
0.8
2881
2910
2939
2967
3051
3315
3554
2995
.3023
.3078
.3133
3389
3106
0.9
3159
.3413
.3186
.3438
.3212
3238
3264
3289
3340
.3365
1.0
.3461
3485
.3508
3531
3577
3599
3621
1.1
.3643
.3665
.3686
.3708
.3729
.3749
3770
3790
.3810
3830
1.2
.3849
.3869
4049
3888
3907
3925
3944
3962
.3980
4147
.3997
4015
1.3
.4032
4066
.4082
.4099
.4115
4131
4162
4177
1.4
.4192
.4207
4222
4236
4251
4265
4394
4279
4292
4306
4319
1.5
.4332
.4345
4357
.4370
4382
4406
4418
4429
4441
1.6
.4452
4463
4474
.4484
4495
4505
4515
4608
4525
4616
.4535
4625
4545
1.7
.4454
.4564
4582
4664
4573
4591
.4599
4633
1.8
.4649
4719
.4641
4671
4738
4706
4767
4656
4678
4686
4693
.4699
1.9
.4713
4726
.4732
4744
4750
.4756
.4761
2.0
.4772
.4778
.4783
.4788
.4793
.4798
4803
4808
4812
.4817
2.1
.4821
.4826
.4830
.4834
4838
4842
4846
.4850
4854
.4857
2.2
.4861
.4864
4871
4901
4868
4878
4890
4916
4875
4881
4884
4887
2.3
.4893
4896
4898
4904
4913
4934
.4951
4906
4909
.4911
2.4
.4918
.4920
.4940
.4922
4941
4925
4927
4929
.4931
4932
4936
2.5
.4938
4943
.4945
4946
.4948
4949
.4952
.4955
.4966
2.6
.4953
4956
4964
4974
4957
4959
4960
4961
4962
4963
2.7
.4965
.4967
.4968
.4969
4970
4971
4972
4973
2.8
.4974
.4975
4976
4977
4977
4979
.4978
4984
4979
4985
4980
4981
4986
2.9
.4981
4982
.4982
4983
4984
.4985
4986
3.0
.4987
4987
4987
.4988
.4988
4989
4989
4989
4990
A990
Note: This table gives the area in the right-hand tail of the distribution (1.e., Z 0). But since the normal
distribution is symmetrical about Z=0, the area in the left-hand tail is the same as the area in the corresponding
right-hand tail. For example, A-1.96 s Zs 0) = 0.4750. Therefore, P(-1.96 s Zs 1.96)- 2(0.4750) 0.95.
tab =
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