I need help with this pleasechoices are is or is not for the first blank and do or do not for the second blank Two different box-filling machines are used on an assembly line. The critical measurement influenced by these machines is the weight of the product inthe boxes. Engineers are quite certain that the variance of the weight of product is o² = 1 ounce. Experiments are conducted using both machines withsample sizes of 64 each. The sample averages for machines A and B are x = 4.7 ounces and x = 4.9 ounces. Engineers are surprised that the twosample averages for the filling machines are so different. Complete parts (a) and (b) below.Click here to view page 1 of the standard normal distribution table.Click here to view page 2 of the standard normal distribution table.(a) Use the Central Limit Theorem to determine P(X-XA≥0.2) under the condition that μ₁ = bP(X-X≥0.2) = 0.1292(b) Do the aforementioned experiments seem to, in any way, strongly support a conjecture that the population means for the two machines are different?Explain using your answer in (a).Since the probability in (a)negligible, the experimentssupport the conjecture.is notis ☑=Areas under the Normal Curvez.00-3.4 0.0003 0.0003 0.0003.01.02.03.04-2.9-2.8-2.7-1.0 0.1587 0.1562 0.1539-0.9 0.1841-0.8 0.2119 0.2090-0.7 0.2420 0.2389-0.6 0.2743 0.2709-0.5 0.3085 0.3050-0.0 0.5000.00.010.4960 0.4920 0.4880 0.4840 0.4801.02.03.04.05.06.070.0003 0.0003 0.0003 0.0003 0.0003-3.3 0.0005 0.0005 0.0005 0.0004 0.0004 0.00040.0004 0.0004-3.2 0.0007 0.0007 0.0006 0.0006 0.0006 0.0006 0.0006 0.0005 0.0005 0.0005 -3.2-3.1 0.0010 0.0009 0.0009 0.0009 0.0008 0.0008 0.0008 0.0008 0.0007 0.0007 -3.1-3.0 0.0013 0.0013 0.0013 0.0012 0.0012 0.0011 0.0011 0.0011 0.0010 0.0010 -3.00.0019 0.0018 0.0018 0.0017 0.0016 0.0016 0.0015 0.0015 0.0014 0.0014 -2.90.0026 0.0025 0.0024 0.0023 0.0023 0.0022 0.0021 0.0021 0.0020 0.0019 -2.80.0035 0.0034 0.0033 0.0032 0.0031 0.0030 0.0029 0.0028 0.0027 0.0026 -2.7-2.6 0.0047 0.0045 0.0044 0.0043 0.0041 0.0040 0.0039 0.0038 0.0037 0.0036 -2.6-2.5 0.0062 0.0060 0.0059 0.0057 0.0055 0.0054 0.0052 0.0051 0.00490.0048 -2.5-2.4 0.0082 0.0080 0.0078 0.0075 0.0073 0.0071 0.0069 0.0068 0.0066 0.0064 -2.4-2.3 0.0107 0.0104 0.0102 0.0099 0.0096 0.0094 0.0091 0.0089 0.0087-2.2 0.0139 0.0136 0.0132 0.0129 0.0125 0.0122 0.0119 0.0116-2.1 0.0179 0.0174 0.0170 0.0166 0.01620.0158 0.0154 0.0150-2.0 0.0228 0.0222 0.0217 0.0212 0.0207 0.0202 0.0197 0.0192-1.9 0.0287 0.0281 0.02740.0268 0.0262 0.0256 0.0250 0.0244-1.8 0.0359 0.0351 0.0344 0.0336 0.0329 0.0322 0.0314 0.0307-1.7 0.0446 0.0436 0.0427 0.0418 0.0409 0.0401 0.0392 0.0384-1.6 0.0548 0.0537 0.0526 0.0516 0.0505 0.0495 0.0485 0.0475-1.5 0.0668 0.0655 0.0643 0.0630 0.0618 0.0606 0.0594 0.0582-1.4 0.0808 0.0793 0.0778 0.0764 0.0749 0.0735 0.0721 0.0708-1.3 0.0968 0.0951 0.0934 0.0918 0.0901 0.0885 0.0869 0.0853-1.2 0.1151 0.1131 0.1112 0.1093 0.1075 0.1056 0.1038 0.1020 0.1003 0.0985 -1.2-1.1 0.1357 0.1335 0.1314 0.1292 0.1271 0.1251 0.1230 0.1210 0.1190 0.1170 -1.10.1515 0.1492 0.1469 0.1446 0.1423 0.1401 0.1379 -1.00.1814 0.1788 0.1762 0.1736 0.1711 0.16850.1635 0.1611 -0.90.16600.2061 0.2033 0.2005 0.1977 0.1949 0.1922 0.1894 0.1867 -0.80.2358 0.2327 0.2296 0.2266 0.2236 0.2206 0.2177 0.2148 -0.70.2676 0.2643 0.2611 0.2578 0.25460.3015 0.2981 0.2946 0.2912 0.2877 0.2843-0.4 0.3446 0.3409 0.3372 0.3336 0.3300 0.3264 0.3228-0.3 0.3821 0.3783 0.3745 0.3707 0.3669 0.3632 0.3594 0.3557 0.3520 0.3483 -0.3-0.2 0.4207 0.4168 0.4129 0.4090 0.4052 0.4013 0.3974 0.3936 0.3897 0.3859 -0.2-0.1 0.4602 0.4562 0.4522 0.4483 0.4443 0.4404 0.4364 0.4325 0.4286 0.4247 -0.10.4761 0.4721 0.4681 0.4641 -0.0.06.07.08.09.080.0003 0.0002 -3.40.0004 0.0003 -3.3.0910Areas under the Normal Curve0.0084 -2.30.01130.0110 -2.20.01460.0143 -2.10.01880.0183 -2.00.02390.0233 -1.90.0301 0.0294 1.80.0375 0.0367 -1.70.0465 0.0455 -1.60.0571 0.0559 -1.50.0694 0.0681 -1.40.0838 0.0823 -1.32.32.42.512.60.25140.2483 0.2451 -0.62.710.2810 0.2776 -0.52.80.3192 0.3156 0.3121 -0.42.9C.0522.00.01.02.03.04.05.070.0 0.5000 0.5040 0.5080 0.5120 0.5160 0.5199 0.5239 0.5279 0.5319 0.5359 0.00.1 0.5398 0.5438 0.5478 0.5517 0.5557 0.5596 0.5636 0.5675 0.5714 0.5753 0.10.2 0.5793 0.5832 0.5871 0.5910 0.5948 0.5987 0.6026 0.6064 0.6103 0.6141 0.20.3 0.6179 0.6217 0.6255 0.6293 0.6331 0.6368 0.6406 0.6443 0.6480 0.6517 0.30.4 0.6554 0.6591 0.6628 0.6664 0.6700 0.6736 0.6772 0.6808 0.6844 0.6879 0.40.5 0.6915 0.6950 0.6985 0.7019 0.7054 0.7088 0.7123 0.7157 0.7190 0.7224 0.50.6 0.7257 0.7291 0.7324 0.7357 0.7389 0.7422 0.7454 0.7486 0.7517 0.7549 0.60.7 0.7580 0.7611 0.7642 0.7673 0.7704 0.7734 0.7764 0.7794 0.7823 0.7852 0.70.8 0.7881 0.7910 0.7939 0.7967 0.7995 0.8023 0.8051 0.8078 0.8106 0.8133 0.80.9 0.8159 0.8186 0.8212 0.8238 0.8264 0.8289 0.8315 0.8340 0.8365 0.8389 0.91.0 0.8413 0.8438 0.8461 0.8485 0.8508 0.8531 0.8554 0.8577 0.8599 0.8621 1.01.1 0.8643 0.8665 0.8686 0.8708 0.8729 0.8749 0.8770 0.8790 0.8810 0.8830 1.11.2 0.8849 0.8869 0.8888 0.8907 0.8925 0.8944 0.8962 0.8980 0.8997 0.9015 1.21.3 0.9032 0.9049 0.9066 0.9082 0.9099 0.9115 0.9131 0.9147 0.9162 0.9177 1.31.4 0.9192 0.9207 0.9222 0.9236 0.9251 0.9265 0.9279 0.9292 0.9306 0.9319 1.41.5 0.9332 0.9345 0.9357 0.9370 0.9382 0.9394 0.9406 0.9418 0.9429 0.9441 1.51.6 0.9452 0.9463 0.9474 0.9484 0.9495 0.9505 0.9515 0.9525 0.9535 0.9545 1.61.7 0.9554 0.9564 0.9573 0.9582 0.9591 0.9599 0.96080.9616 0.9625 0.9633 1.71.8 0.9641 0.9649 0.9656 0.9664 0.9671 0.9678 0.9686 0.9693 0.9699 0.9706 1.81.9 0.9713 0.9719 0.9726 0.9732 0.9738 0.9744 0.9750 0.9756 0.9761 0.9767 1.92.0 0.9772 0.9778 0,9783 0.9788 0.9793 0.9798 0.9803 0.9808 0.9812 0.9817 2.02.1 0.9821 0.9826 0.9830 0.9834 0.9838 0.9842 0.9846 0.9850 0.9854 0.9857 2.12.2 0.9861 0.9864 0.9868 0.9871 0.9875 0.9878 0.9881 0.9884 0.9887 0.9890 2.20.9893 0.9896 0.9898 0.9901 0.9904 0.9906 0.9909 0.9911 0.9913 0.9916 2.30.99340.99180.99220.99200.99250.99290.99270.9931 0.99320.9936 2.40.9938 0.9940 0.9941 0.9943 0.9945 0.9946 0.9948 0.9949 0.9951 0.9952 2.50.9953 0.9955 0.9956 0.9957 0.9959 0.9960 0.9961 0.9962 0.9963 0.9964 2.60.9965 0.9966 0.9967 0.9968 0.9969 0.99700.9971 0.9972 0.9973 0.99740.9974 0.9975 0.9976 0.9977 0.9977 0.99780.9981 0.9982 0.9982 0.9983 0.9984 0.99843.0 0.9987 0.9987 0.9987 0.9988 0.9988 0.99893.1 0.9990 0.9991 0.9991 0.9991 0.9992 0.99923.2 0.9993 0.9993 0.9994 0.9994 0.99943.3 0.9995 0.9995 0.9995 0.99963.4 0.9997 0.9997 0.9997 0.9997 0.9997.00.01.02.03.04.06.08.092.052.70.9979 0.9979 0.9980 0.9981 2.80.9985 0.9985 0.9986 0.9986 2.90.9989 0.9989 0.9990 0.9990 3.00.9992 0.9992 0.9993 0.9993 3.10.9994 0.9994 0.9995 0.9995 0.9995 3.20.9996 0.9996 0.9996 0.9996 0.9996 0.99973.30.9997 0.9997 0.9997 0.9997 0.9998 3.4.06.07.08.09Q

Two different box-filling machines are used on an assembly line. The critical measurement influenced by these machines is the weight of the product in the boxes. Engineers are quite certain that the variance of the weight of product is o² = 1 ounce. Experiments are conducted using both machines with sample sizes of 64 each. The sample averages for machines A and B are x = 4.7 ounces and x = 4.9 ounces. Engineers are surprised that the two sample averages for the filling machines are so different. Complete parts (a) and (b) below. Click here to view page 1 of the standard normal distribution table. Click here to view page 2 of the standard normal distribution table. (a) Use the Central Limit Theorem to determine P(X-X≥0.2) under the condition that H₁ = H P(X-X≥0.2) = 0.1292 (b) Do the aforementioned experiments seem to, in any way, strongly support a conjecture that the population means for the two machines are different? Explain using your answer in (a). Since the probability in (a) negligible, the experiments support the conjecture. is not is