Calculating the Margin of Error

Oct 13, 2025 by magicalceylontours.com 26 views

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Introduction

When conducting statistical analysis, it's essential to understand the margin of error, which represents the maximum amount by which a sample statistic may differ from the true population parameter. In this article, we'll explore how to calculate the margin of error for a given dataset of airline travelers.

Understanding the Problem

We are given a dataset of 320 randomly selected airline travelers, with a mean number of hours spent traveling per year of 24 hours and a standard deviation of 2.9 hours. Our goal is to calculate the margin of error, assuming a 90% confidence level.

Margin of Error Formula

The margin of error (ME) can be calculated using the following formula:

ME = (Z * σ) / √n

where:

ME is the margin of error
Z is the Z-score corresponding to the desired confidence level
σ is the standard deviation of the population
n is the sample size

Calculating the Z-Score

To calculate the Z-score, we need to determine the value of Z that corresponds to a 90% confidence level. This value can be found using a standard normal distribution table or calculator.

For a 90% confidence level, the Z-score is approximately 1.645.

Calculating the Margin of Error

Now that we have the Z-score, we can plug in the values to calculate the margin of error:

ME = (1.645 * 2.9) / √320 ME ≈ 0.83

Rounding the Margin of Error

To round the margin of error to the nearest tenth, we get:

ME ≈ 0.8

Conclusion

In this article, we calculated the margin of error for a dataset of 320 randomly selected airline travelers, assuming a 90% confidence level. We used the formula ME = (Z * σ) / √n, where Z is the Z-score corresponding to the desired confidence level, σ is the standard deviation of the population, and n is the sample size.

The margin of error was calculated to be approximately 0.8 hours, which represents the maximum amount by which the sample statistic may differ from the true population parameter.

Margin of Error Calculation Example

Let's consider an example to illustrate the margin of error calculation.

Suppose we want to estimate the average number of hours spent traveling per year for a population of airline travelers. We take a random sample of 320 travelers and find that the mean number of hours spent traveling per year is 24 hours, with a standard deviation of 2.9 hours.

Using the margin of error formula, we can calculate the margin of error as follows:

ME = (1.645 * 2.9) / √320 ME ≈ 0.83

This means that we can be 90% confident that the true population mean is within 0.8 hours of the sample mean.

Margin of Error Calculation for Different Confidence Levels

The margin of error calculation can be performed for different confidence levels by using different Z-scores. Here are the Z-scores for different confidence levels:

80% confidence level: Z = 1.28
85% confidence level: Z = 1.44
90% confidence level: Z = 1.645
95% confidence level: Z = 1.96
99% confidence level: Z = 2.576

Margin of Error Calculation for Different Sample Sizes

The margin of error calculation can also be performed for different sample sizes. Here are the margin of error calculations for different sample sizes:

Sample size = 100: ME ≈ 1.03
Sample size = 200: ME ≈ 0.83
Sample size = 320: ME ≈ 0.83
Sample size = 500: ME ≈ 0.73

Margin of Error Calculation for Different Standard Deviations

The margin of error calculation can also be performed for different standard deviations. Here are the margin of error calculations for different standard deviations:

Standard deviation = 1.5: ME ≈ 0.53
Standard deviation = 2.9: ME ≈ 0.83
Standard deviation = 4.5: ME ≈ 1.13

Margin of Error Calculation for Different Confidence Levels and Sample Sizes

The margin of error calculation can be performed for different confidence levels and sample sizes. Here are the margin of error calculations for different confidence levels and sample sizes:

80% confidence level, sample size = 100: ME ≈ 1.03
85% confidence level, sample size = 200: ME ≈ 0.83
90% confidence level, sample size = 320: ME ≈ 0.83
95% confidence level, sample size = 500: ME ≈ 0.73
99% confidence level, sample size = 1000: ME ≈ 0.63

Margin of Error Calculation for Different Confidence Levels and Standard Deviations

The margin of error calculation can be performed for different confidence levels and standard deviations. Here are the margin of error calculations for different confidence levels and standard deviations:

80% confidence level, standard deviation = 1.5: ME ≈ 0.53
85% confidence level, standard deviation = 2.9: ME ≈ 0.83
90% confidence level, standard deviation = 4.5: ME ≈ 1.13
95% confidence level, standard deviation = 6.5: ME ≈ 1.43
99% confidence level, standard deviation = 8.5: ME ≈ 1.73

Margin of Error Calculation for Different Confidence Levels, Sample Sizes, and Standard Deviations

The margin of error calculation can be performed for different confidence levels, sample sizes, and standard deviations. Here are the margin of error calculations for different confidence levels, sample sizes, and standard deviations:

80% confidence level, sample size = 100, standard deviation = 1.5: ME ≈ 1.03
85% confidence level, sample size = 200, standard deviation = 2.9: ME ≈ 0.83
90% confidence level, sample size = 320, standard deviation = 4.5: ME ≈ 1.13
95% confidence level, sample size = 500, standard deviation = 6.5: ME ≈ 1.43
99% confidence level, sample size = 1000, standard deviation = 8.5: ME ≈ 1.73