Determining the Area Under the Standard Normal Curve

Oct 13, 2025 by windailys.com 79 views

Introduction

The standard normal curve, also known as the z-distribution, is a fundamental concept in statistics and probability theory. It is a continuous probability distribution that is symmetric about the mean, with a standard deviation of 1. The standard normal curve is used to model a wide range of phenomena, from the heights of individuals in a population to the returns on investments in a portfolio. In this article, we will explore how to determine the area under the standard normal curve that lies between specific z-scores.

The Standard Normal Curve

The standard normal curve is a probability distribution that is characterized by the following properties:

It is symmetric about the mean, which is 0.
It has a standard deviation of 1.
It is continuous, meaning that it can take on any value within a given range.
It is bell-shaped, with the majority of the data points clustered around the mean.

The standard normal curve is often represented by the following equation:

f(z) = (1/√(2π)) * e^(-z2/2)

where f(z) is the probability density function of the standard normal curve, and z is the z-score.

Determining the Area Under the Standard Normal Curve

To determine the area under the standard normal curve that lies between specific z-scores, we can use a standard normal distribution table, also known as a z-table. The z-table provides the probability that a random variable will take on a value less than or equal to a given z-score.

Method 1: Using the z-Table

The z-table is a table that lists the probabilities of a random variable taking on a value less than or equal to a given z-score. To use the z-table, we need to find the z-score in the table and then look up the corresponding probability.

For example, let's say we want to find the area under the standard normal curve that lies between z = -2.12 and z = 2.12. We can use the z-table to find the probabilities of a random variable taking on a value less than or equal to z = -2.12 and z = 2.12.

z-score	Probability
-2.12	0.0170
2.12	0.9830

The probability of a random variable taking on a value less than or equal to z = -2.12 is 0.0170, and the probability of a random variable taking on a value less than or equal to z = 2.12 is 0.9830.

To find the area under the standard normal curve that lies between z = -2.12 and z = 2.12, we can subtract the probability of a random variable taking on a value less than or equal to z = -2.12 from the probability of a random variable taking on a value less than or equal to z = 2.12.

Area = 0.9830 - 0.0170 = 0.9660

Therefore, the area under the standard normal curve that lies between z = -2.12 and z = 2.12 is 0.9660.

Method 2: Using a Calculator or Software

Alternatively, we can use a calculator or software to find the area under the standard normal curve that lies between specific z-scores. For example, we can use a calculator or software to find the area under the standard normal curve that lies between z = -2.12 and z = 2.12.

Using a calculator or software, we can find that the area under the standard normal curve that lies between z = -2.12 and z = 2.12 is 0.9660.

Example 1: Finding the Area Between z = -1.65 and z = 0

Let's say we want to find the area under the standard normal curve that lies between z = -1.65 and z = 0. We can use the z-table to find the probabilities of a random variable taking on a value less than or equal to z = -1.65 and z = 0.

z-score	Probability
-1.65	0.0505
0	0.5000

The probability of a random variable taking on a value less than or equal to z = -1.65 is 0.0505, and the probability of a random variable taking on a value less than or equal to z = 0 is 0.5000.

To find the area under the standard normal curve that lies between z = -1.65 and z = 0, we can subtract the probability of a random variable taking on a value less than or equal to z = -1.65 from the probability of a random variable taking on a value less than or equal to z = 0.

Area = 0.5000 - 0.0505 = 0.4495

Therefore, the area under the standard normal curve that lies between z = -1.65 and z = 0 is 0.4495.

Example 2: Finding the Area Between z = -0.31 and z = 0.04

Let's say we want to find the area under the standard normal curve that lies between z = -0.31 and z = 0.04. We can use the z-table to find the probabilities of a random variable taking on a value less than or equal to z = -0.31 and z = 0.04.

z-score	Probability
-0.31	0.3740
0.04	0.5244

The probability of a random variable taking on a value less than or equal to z = -0.31 is 0.3740, and the probability of a random variable taking on a value less than or equal to z = 0.04 is 0.5244.

To find the area under the standard normal curve that lies between z = -0.31 and z = 0.04, we can subtract the probability of a random variable taking on a value less than or equal to z = -0.31 from the probability of a random variable taking on a value less than or equal to z = 0.04.

Area = 0.5244 - 0.3740 = 0.1504

Therefore, the area under the standard normal curve that lies between z = -0.31 and z = 0.04 is 0.1504.

Conclusion

In conclusion, the standard normal curve is a fundamental concept in statistics and probability theory. It is a continuous probability distribution that is symmetric about the mean, with a standard deviation of 1. The standard normal curve is used to model a wide range of phenomena, from the heights of individuals in a population to the returns on investments in a portfolio.

In this article, we have explored how to determine the area under the standard normal curve that lies between specific z-scores. We have used the z-table to find the probabilities of a random variable taking on a value less than or equal to a given z-score, and we have used a calculator or software to find the area under the standard normal curve that lies between specific z-scores.

References

Moore, D. S., & McCabe, G. P. (2013). Introduction to the practice of statistics. W.H. Freeman and Company.
Ross, S. M. (2014). Introduction to probability models. Academic Press.
Johnson, N. L., & Kotz, S. (1970). Continuous univariate distributions. Houghton Mifflin Company.
Frequently Asked Questions: Determining the Area Under the Standard Normal Curve ====================================================================================

Q: What is the standard normal curve?

A: The standard normal curve, also known as the z-distribution, is a continuous probability distribution that is symmetric about the mean, with a standard deviation of 1. It is used to model a wide range of phenomena, from the heights of individuals in a population to the returns on investments in a portfolio.

Q: How do I determine the area under the standard normal curve that lies between specific z-scores?

A: To determine the area under the standard normal curve that lies between specific z-scores, you can use a standard normal distribution table, also known as a z-table. The z-table provides the probability that a random variable will take on a value less than or equal to a given z-score.

Q: What is the z-table?

A: The z-table is a table that lists the probabilities of a random variable taking on a value less than or equal to a given z-score. It is used to determine the area under the standard normal curve that lies between specific z-scores.

Q: How do I use the z-table to find the area under the standard normal curve that lies between specific z-scores?

A: To use the z-table, you need to find the z-score in the table and then look up the corresponding probability. The probability of a random variable taking on a value less than or equal to a given z-score is listed in the table.

Q: Can I use a calculator or software to find the area under the standard normal curve that lies between specific z-scores?

A: Yes, you can use a calculator or software to find the area under the standard normal curve that lies between specific z-scores. Many calculators and software programs have built-in functions to calculate the area under the standard normal curve.

Q: What is the difference between the area under the standard normal curve and the probability of a random variable taking on a value less than or equal to a given z-score?

A: The area under the standard normal curve is the total area under the curve, while the probability of a random variable taking on a value less than or equal to a given z-score is the area under the curve to the left of the z-score.

Q: How do I find the area under the standard normal curve that lies between two z-scores?

A: To find the area under the standard normal curve that lies between two z-scores, you can subtract the probability of a random variable taking on a value less than or equal to the lower z-score from the probability of a random variable taking on a value less than or equal to the higher z-score.

Q: What is the significance of the standard normal curve in statistics and probability theory?

A: The standard normal curve is a fundamental concept in statistics and probability theory. It is used to model a wide range of phenomena, from the heights of individuals in a population to the returns on investments in a portfolio.

Q: Can I use the standard normal curve to model real-world phenomena?

A: Yes, you can use the standard normal curve to model real-world phenomena. The standard normal curve is a continuous probability distribution that can be used to model a wide range of phenomena.

Q: What are some common applications of the standard normal curve?

A: Some common applications of the standard normal curve include:

Modeling the heights of individuals in a population
Modeling the returns on investments in a portfolio
Modeling the scores on a standardized test
Modeling the time it takes to complete a task

Q: How do I choose the right z-score to use in a problem?

A: To choose the right z-score to use in a problem, you need to consider the specific problem and the data that is available. You should choose a z-score that is relevant to the problem and that will provide the most accurate results.

Q: What are some common mistakes to avoid when using the standard normal curve?

A: Some common mistakes to avoid when using the standard normal curve include:

Using the wrong z-score
Not considering the specific problem and data
Not using the correct probability distribution
Not considering the assumptions of the standard normal curve

Q: How do I troubleshoot common problems when using the standard normal curve?

A: To troubleshoot common problems when using the standard normal curve, you should:

Check the z-score and make sure it is correct
Check the data and make sure it is relevant to the problem
Check the probability distribution and make sure it is correct
Check the assumptions of the standard normal curve and make sure they are met

Conclusion

To determine the area under the standard normal curve that lies between specific z-scores, you can use a standard normal distribution table, also known as a z-table. The z-table provides the probability that a random variable will take on a value less than or equal to a given z-score.

Alternatively, you can use a calculator or software to find the area under the standard normal curve that lies between specific z-scores. Many calculators and software programs have built-in functions to calculate the area under the standard normal curve.

References

Moore, D. S., & McCabe, G. P. (2013). Introduction to the practice of statistics. W.H. Freeman and Company.
Ross, S. M. (2014). Introduction to probability models. Academic Press.
Johnson, N. L., & Kotz, S. (1970). Continuous univariate distributions. Houghton Mifflin Company.