Suppose you are examining a set of raw medical data that includes the side effects of a specific drug. You are interested in finding out which side effects occur the most often. What would be an appropriate algorithm to find this data?(1 point)%0D%0AResponses%0D%0A%0D%0Afor loop%0D%0Afor loop%0D%0A%0D%0Abinary search%0D%0Abinary search%0D%0A%0D%0Abubble sort%0D%0Abubble sort%0D%0A%0D%0Alinear search
A linear search algorithm would be an appropriate choice to find the side effects that occur most often in the raw medical data. This algorithm involves scanning each data element in order and comparing it to the desired value. By iterating through the set of data and keeping a count of each side effect occurrence, the algorithm can determine which side effects occur the most frequently.
To find the side effect that occurs most often in a set of raw medical data, you can use the algorithm called "linear search". Here's how you can implement it:
1. Start by initializing a variable to keep track of the current maximum occurrence of a side effect. Let's call it "maxCount" and set it to 0 initially.
2. Iterate through each side effect in the dataset using a for loop. For each side effect:
a. Initialize a counter variable to keep track of the occurrence of that side effect. Let's call it "count" and set it to 0 initially.
b. Iterate through the dataset again using another for loop to compare each side effect with every other side effect.
c. If a match is found, increment the count variable by 1.
d. After the inner loop ends, check if the count variable is greater than the current maxCount. If it is, update maxCount to the value of count and store the corresponding side effect in a separate variable called "mostOccurringSideEffect".
3. After the outer loop ends, you will have the side effect that occurs most often stored in the "mostOccurringSideEffect" variable.
The linear search algorithm compares each side effect with every other side effect in the dataset, keeping track of the occurrence count for each. It is a simple and straightforward approach to find the most frequently occurring side effect from the given dataset.
An appropriate algorithm to find the most common side effects in raw medical data would be a combination of a for loop and a linear search.
1. Initialize an empty dictionary to store each side effect as a key and its occurrence count as a value.
2. Iterate through each data entry in the medical data using a for loop.
3. For each entry, access the side effects data and check if the side effect is already a key in the dictionary.
4. If the side effect is not in the dictionary, add it as a new key and set its value to 1.
5. If the side effect is already a key in the dictionary, increment its value by 1.
6. Finally, after iterating through all the data, iterate through the dictionary to find the side effect with the highest occurrence count.
This approach allows you to count how many times each side effect appears in the data and identify the most common side effects.