Mean
Standard deviation
Sample size
Confidence level
%
Confidence interval
Lower bound
Upper bound
Confidence interval (±)

This confidence interval calculator is a tool that will help you find the confidence interval for a sample of given mean, standard deviation and size. You can use it with any arbitrary confidence level. If you want to know what exactly the confidence interval is and how to calculate it, or are looking for the 95 confidence interval formula, this article is bound to help you.

What is the confidence interval?

The definition says that "a confidence interval is a range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter." But what does that mean in reality?

Imagine a producer of bricks who is concerned whether the mass of bricks he manufactures agrees with the specifications. He has measured the average mass of a sample of 100 bricks to be equal to 3 kg. He has also found the 95% confidence interval to be between 2.85 kg and 3.15 kg. It means that he can be 95% sure that the average mass of all bricks he manufactured lies between 2.85 kg and 3.15 kg.

Of course, you don't always want to be exactly 95% sure. You might want to be 99% certain, or maybe it is enough for you that the confidence interval is correct in 90% of cases. This percentage is called the confidence level.

95 confidence interval formula

Calculating the confidence interval requires you to know three parameters of your sample: the mean (average) value μ, the standard deviation σ and the sample size n (number of measurements taken). Then, you can calculate the margin of error according to the following formulas:

standard error = σ/√n

margin of error = standard error * Z(0.95)

where Z(0.95) is the z-score corresponding to the confidence level of 95%. If you are using a different confidence level, you need to calculate the appropriate z-score instead of this value.

How to find the Z(0.95) value? It is the value of z-score for which the two-tailed confidence level is equal to 95%. It means that if you draw a normal distribution curve, the area between the z-score and the opposite of z-score will be equal to 0.95.

If you want to calculate this value using the z-score tables, this is what you need to do:

  1. Decide on your confidence level. Let's assume it is 95%.
  2. Calculate what is the probability that your result won't be in the confidence interval. This value is equal to 100% - 95% = 5%.
  3. Take a look at the normal distribution curve. 95% is the area in the middle. That means that the area to the left of the opposite of your z-score is equal to 0.025 (2.5%) and the area to the right to your z-score is also equal to 0.025 (2.5%).
  4. Area to the right to your z-score is exactly the same as the p-value of your z-score. You can use the tables to find the z-score that corresponds to 0.025 p-value. In this case, it is 1.959.

Once you have calculated the Z(0.95) value, you can simply input this value into the equation above to get the margin of error. Now, the only thing left to do is to find the lower and upper bound of the confidence interval:

lower bound = mean - margin of error

upper bound = mean + margin of error

How to calculate confidence interval: an example

Luckily, our confidence level calculator can perform all of these calculations on its own. All you need to do is follow these steps to find the confidence interval.

  1. Decide on the mean value of your sample. Let's assume that we are solving the brick example and the mean mass of a brick is 3 kg.
  2. Determine the standard deviation of the sample. Let's say it is equal to 0.5 kg.
  3. Write down the sample size. Let's say your calculations were based on a sample of 100 bricks.
  4. Determine your confidence level. You can leave it at a default value of 95%.
  5. Our confidence interval calculator automatically finds the Z(0.95) score equal to 1.959.
  6. Find the standard error equal to σ/√n = 0.5/√100 = 0.05.
  7. Multiply this value by the Z(0.95) score to obtain the margin of error: 0.05 * 1.959 = 0.098.
  8. Now all you have to do is to add or subtract the margin of error from the mean value to obtain the confidence interval. In this case, the confidence interval is between 2.902 kg and 3.098 kg.
Bogna Haponiuk

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