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I really need help with a C program. The input file is mpn_input and looks like this 0-1-0 12 7 23 0-2-1 13 9 33

I really need help with a C program.

image text in transcribedimage text in transcribedimage text in transcribed

The input file is mpn_input and looks like this

0-1-0 12 7 23 0-2-1 13 9 33 1-0-0 13 7 30 1-0-1 15 5 32 1-1-1 11 2 21 1-0-2 17 5 35 1-1-2 15 8 36 1-1-0 15 9 33 2-0-0 17 6 35 2-1-0 20 9 45 2-1-1 17 2 33 2-0-2 15 5 27 2-2-0 25 11 50 2-2-1 20 8 39 3-0-1 22 11 41 3-0-2 18 8 26 3-1-2 19 3 25 3-3-2 32 15 53 4-1-0 20 9 45 4-2-0 22 9 56 4-2-1 26 12 65 4-3-0 28 13 77 4-3-1 30 15 78 4-4-0 40 20 86 5-0-0 30 22 110 5-0-1 50 20 140 5-0-2 55 22 150 5-1-0 60 30 180 5-1-1 50 20 170 5-1-2 70 30 210 5-2-0 75 35 220 5-2-1 90 40 250 5-2-2 80 30 250 5-3-0 110 40 300 5-3-1 130 42 330 5-3-2 140 60 360

and the output needs to look like this:

image text in transcribed

Thank You in advance!

Scenario Microbiologists estimating the number of bacteria in a sample that contains bacteria that do not grow well on solid media may use a statistical technique called the most probable number (MPN) method. Each of five tubes of nutrient medium receives 10 ml of the sample. A second set of five tubes receives 1 ml of sample per tube, and in each of a third set of five tubes, only 0.1 ml of sample is placed. Each tube in which bacterial growth is observed is recorded as a positive, and the numbers for the three groups are combined to create a triplet such as 5-2-1, which means that all five tubes receiving 10 ml of sample show bacterial growth, only two tubes in the 1-ml group show growth, and only one of the 0.1-ml group is positive. A microbiologist would use this combination-of-positive triplet as an index to a table like the one below to determine that the most probable number of bacteria per 100 ml of the sample is 70, and 95 percent of the samples yielding this triplet contain between 30 and 210 bacteria per 100 ml Table of Bacterial Concentrations for Most Probable Number Method Combination of Positives MPN Index/100 ml 95 percent Confidence Limits 4-2-0 4-2-1 4-3-D 4-3-1 Upper 56 65 67 26 12 27 15 34 110 140 120 150 180 5-0-1 30 20 10 20 5-0-2 50 170 5-2-0 5-2-1 5-2-2 5-3-0 5-3-1 5-3-2 50 70 90 210 30 250 110 140 360 Problem Define a structure type to represent one row of the MPN table. The structure will include one string component for the combination-of-positives triplet and three integer components in which to store the associated most probable mumber and the lower and upper bounds of the 95 percent confidence range. Scenario Microbiologists estimating the number of bacteria in a sample that contains bacteria that do not grow well on solid media may use a statistical technique called the most probable number (MPN) method. Each of five tubes of nutrient medium receives 10 ml of the sample. A second set of five tubes receives 1 ml of sample per tube, and in each of a third set of five tubes, only 0.1 ml of sample is placed. Each tube in which bacterial growth is observed is recorded as a positive, and the numbers for the three groups are combined to create a triplet such as 5-2-1, which means that all five tubes receiving 10 ml of sample show bacterial growth, only two tubes in the 1-ml group show growth, and only one of the 0.1-ml group is positive. A microbiologist would use this combination-of-positive triplet as an index to a table like the one below to determine that the most probable number of bacteria per 100 ml of the sample is 70, and 95 percent of the samples yielding this triplet contain between 30 and 210 bacteria per 100 ml Table of Bacterial Concentrations for Most Probable Number Method Combination of Positives MPN Index/100 ml 95 percent Confidence Limits 4-2-0 4-2-1 4-3-D 4-3-1 Upper 56 65 67 26 12 27 15 34 110 140 120 150 180 5-0-1 30 20 10 20 5-0-2 50 170 5-2-0 5-2-1 5-2-2 5-3-0 5-3-1 5-3-2 50 70 90 210 30 250 110 140 360 Problem Define a structure type to represent one row of the MPN table. The structure will include one string component for the combination-of-positives triplet and three integer components in which to store the associated most probable mumber and the lower and upper bounds of the 95 percent confidence range

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