Finding the Proportion of a Normal Distribution

Oct 13, 2025 by talynt.org 47 views

The normal distribution, also known as the Gaussian distribution or bell curve, is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In this distribution, the majority of the data points cluster around the mean, and the probability of data points decreases as you move further away from the mean. The z-score is a measure of how many standard deviations an element is from the mean. In this article, we will explore the concept of z-scores and how to find the proportion of a normal distribution located between the mean and a given z-score.

What is a Z-Score?

A z-score is a measure of how many standard deviations an element is from the mean. It is calculated by subtracting the mean from the value and then dividing by the standard deviation. The z-score formula is:

z = (X - μ) / σ

Where:

z is the z-score
X is the value of the element
μ is the mean of the distribution
σ is the standard deviation of the distribution

Understanding the 68-95-99.7 Rule

The 68-95-99.7 rule, also known as the empirical rule, states that in a normal distribution, about 68% of the data falls within one standard deviation of the mean, about 95% falls within two standard deviations, and about 99.7% falls within three standard deviations. This rule can be used to estimate the proportion of data points within a certain range of the mean.

Finding the Proportion of a Normal Distribution

To find the proportion of a normal distribution located between the mean and a given z-score, we can use a standard normal distribution table or a calculator. The standard normal distribution table shows the area to the left of a given z-score. To find the proportion between the mean and a given z-score, we need to find the area to the left of the z-score and then subtract the area to the left of the mean.

Calculating the Proportion

Let's calculate the proportion of a normal distribution located between the mean and z = 1.40.

First, we need to find the area to the left of z = 1.40. Using a standard normal distribution table, we find that the area to the left of z = 1.40 is approximately 0.9192.

Next, we need to find the area to the left of the mean. Since the normal distribution is symmetric about the mean, the area to the left of the mean is 0.5.

Now, we can find the proportion of the normal distribution located between the mean and z = 1.40 by subtracting the area to the left of the mean from the area to the left of z = 1.40:

Proportion = Area to the left of z = 1.40 - Area to the left of the mean Proportion = 0.9192 - 0.5 Proportion = 0.4192

Therefore, the proportion of a normal distribution located between the mean and z = 1.40 is approximately 0.4192.

Conclusion

In conclusion, the normal distribution is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. The z-score is a measure of how many standard deviations an element is from the mean. To find the proportion of a normal distribution located between the mean and a given z-score, we can use a standard normal distribution table or a calculator. In this article, we calculated the proportion of a normal distribution located between the mean and z = 1.40 and found that it is approximately 0.4192.

References

Moore, D. S., & McCabe, G. P. (2013). Introduction to the practice of statistics (6th ed.). New York: W.H. Freeman and Company.
Ross, S. M. (2012). Introduction to probability models (10th ed.). San Diego: Academic Press.

Discussion

What is the proportion of a normal distribution located between the mean and z = 1.80? Use a standard normal distribution table or a calculator to find the answer.

Answer

To find the proportion of a normal distribution located between the mean and z = 1.80, we need to find the area to the left of z = 1.80 and then subtract the area to the left of the mean.

Using a standard normal distribution table, we find that the area to the left of z = 1.80 is approximately 0.9646.

Next, we need to find the area to the left of the mean. Since the normal distribution is symmetric about the mean, the area to the left of the mean is 0.5.

Now, we can find the proportion of the normal distribution located between the mean and z = 1.80 by subtracting the area to the left of the mean from the area to the left of z = 1.80:

Proportion = Area to the left of z = 1.80 - Area to the left of the mean Proportion = 0.9646 - 0.5 Proportion = 0.4646

In this article, we will answer some frequently asked questions about normal distribution and z-scores.

Q: What is the normal distribution?

A: The normal distribution, also known as the Gaussian distribution or bell curve, is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean.

Q: What is a z-score?

A: A z-score is a measure of how many standard deviations an element is from the mean. It is calculated by subtracting the mean from the value and then dividing by the standard deviation.

Q: How do I calculate a z-score?

A: To calculate a z-score, you need to know the value of the element, the mean of the distribution, and the standard deviation of the distribution. The z-score formula is:

z = (X - μ) / σ

Where:

z is the z-score
X is the value of the element
μ is the mean of the distribution
σ is the standard deviation of the distribution

Q: What is the 68-95-99.7 rule?

A: The 68-95-99.7 rule, also known as the empirical rule, states that in a normal distribution, about 68% of the data falls within one standard deviation of the mean, about 95% falls within two standard deviations, and about 99.7% falls within three standard deviations.

Q: How do I find the proportion of a normal distribution located between the mean and a given z-score?

A: To find the proportion of a normal distribution located between the mean and a given z-score, you can use a standard normal distribution table or a calculator. The standard normal distribution table shows the area to the left of a given z-score. To find the proportion between the mean and a given z-score, you need to find the area to the left of the z-score and then subtract the area to the left of the mean.

Q: What is the proportion of a normal distribution located between the mean and z = 1.40?

A: To find the proportion of a normal distribution located between the mean and z = 1.40, we need to find the area to the left of z = 1.40 and then subtract the area to the left of the mean. Using a standard normal distribution table, we find that the area to the left of z = 1.40 is approximately 0.9192. The area to the left of the mean is 0.5. Therefore, the proportion of a normal distribution located between the mean and z = 1.40 is approximately 0.4192.

Q: What is the proportion of a normal distribution located between the mean and z = 1.80?

A: To find the proportion of a normal distribution located between the mean and z = 1.80, we need to find the area to the left of z = 1.80 and then subtract the area to the left of the mean. Using a standard normal distribution table, we find that the area to the left of z = 1.80 is approximately 0.9646. The area to the left of the mean is 0.5. Therefore, the proportion of a normal distribution located between the mean and z = 1.80 is approximately 0.4646.

Q: How do I use a standard normal distribution table?

A: A standard normal distribution table shows the area to the left of a given z-score. To use the table, you need to find the z-score in the table and then read the corresponding area to the left of the z-score.

Q: What are some common z-scores?

A: Some common z-scores include:

z = 0: This is the mean of the distribution.
z = 1: This is one standard deviation above the mean.
z = -1: This is one standard deviation below the mean.
z = 2: This is two standard deviations above the mean.
z = -2: This is two standard deviations below the mean.

Q: How do I interpret a z-score?

A: A z-score can be interpreted as follows:

A positive z-score indicates that the value is above the mean.
A negative z-score indicates that the value is below the mean.
A z-score of 0 indicates that the value is equal to the mean.
A z-score of 1 indicates that the value is one standard deviation above the mean.
A z-score of -1 indicates that the value is one standard deviation below the mean.

Conclusion

In conclusion, the normal distribution and z-scores are important concepts in statistics. Understanding these concepts can help you to analyze and interpret data. We hope that this article has helped you to understand the normal distribution and z-scores better. If you have any further questions, please don't hesitate to ask.