Hello, Is it possible for the same person that assisted me with the similar prob

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Hello,

Is it possible for the same person that assisted me with the similar problem/topic below on July 6, assist me again with the one below. If someone else will assist, please ensure 100% accuracy and confident answer is accurate. Thanks so much.

Page 1.

Analyze the performance of three scheduling mechanisms: Exponential Averaging, MLFQ, and true ShortestBurstFirst.   Calculate the Average Completion Time AND count the number of context switches.   The workload consists of the following:

P1: 10(3,2,4); P2: 4(2,6); P3: 16(2,4,5,6).      I/O between bursts for 4 time quantums.   Exp Ave default =2, alpha=0.6

MLFQ: 3 queues of 2,3 and 4 quantums for the queues. Processes are executed in FIFO order within each queue.

Executing (initial pred=2, alpha =0.6)

Time

0

Exec

Ready

1,2,3

P1

2

P2

2

P3

2

I/O:4

Ave completion time =       Context switches =

MLFQ: Executing in Queues

Time

0

Q1:1

Q2:2

Q3:4

MLFQ: In Queues

Q1

1,2,3

Q2

Q3

IO:4

Ave Completion Time =        Context switches =

True SJF:

Time

0

Executing

ReadyQ

1,2,3

I/O:4

Completion time ave =                                                            .   Context switches =    

Executing (initial pred=2, alpha =0.6)

Time

0

Exec

Ready

1,2,3

P1

2

P2

2

P3

2

I/O:4

Explanation / Answer

he first thing to understand is the difference between confidence levels and margins of error. Simply put, a confidence level describes how sure you can be that your results are accurate, whereas the margin of error shows the range the survey results would fall between if our confidence level held true. A standard survey will usually have a confidence level of 95% and margin of error of 5%.

Here is an example of a confidence level and margin of error at work. Let’s say we own a magazine with 1000 subscribers and we want to measure their satisfaction. After plugging in our information in the Survey Sample Size Calculator, we know that a sample size of 278 people gives us a confidence level of 95% with a margin of error of 5%. Our 95% confidence level states that 19 out of 20 times we conduct this survey our results would land within our margin of error. Our 5% margin of error says that if we surveyed all 1000 subscribers, the results could differ with a score of minus 5% or plus 5% from its original score.

For the purpose of this example, let’s say we asked our respondents to rate their satisfaction with our magazine on a scale from 0-10 and it resulted in a final average score of 8.6. With our allotted margin of error and confidence level we can be 95% certain that if we surveyed all 1000 subscribers that our average score would be between 8.1-9.1.

What Happens When Your Sample Size is too Low?

Now that we know how both margins of error and confidence levels affect the accuracy of results, let’s take a look at what happens when the sample size changes. The lower your sample size, the higher your margin of error and lower your confidence level. This means that your data is becoming less reliable.

If we continue with our example and decide to lower our number of responses to 158, we’ll see a significant drop in our confidence level. Now our level of confidence has lowered to 90%, with a margin of error of 6%. So with the same satisfaction score of 8.6, we’d now only have a 9 in 10 chance of our results falling between a score of 8.0-9.2 if we surveyed all 1000 subscribers.

What if Your Sample Size is too High?

Theoretically speaking a sample size can never be too high. Unfortunately, it is sometimes much more expensive to incentivize or convince your target audience to take part. This could be expensive, and from a statistical perspective, ultimately frivolous. In some surveys, a high confidence level and low margin of error are easier to achieve based on the availability and size of your target audience. But most surveys, especially those involving the general public, a high number of responses can be difficult to achieve.

For these reasons, there exists the standard confidence level of 95% with a margin of error of either 5% or 2.5%. In the end, attempting to go beyond this level of accuracy could be unrealistic and ultimately a less beneficial priority than focusing on making sure your respondents are valid for your survey and are giving truthful responses.

How does the Calculator Work?

So you’re probably wondering how to figure out how the Calculator determines what your sample size should be. Well, all you need is your desired confidence level and margin of error, as well as the number of people that make up your total population size. After plugging these three numbers into the Survey Sample Size Calculator, it conducts two survey sample size formulas for you and comes up with the appropriate number of responses. But just so you know the math behind it, here are the formulas used to calculate sample size:

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