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Z Critical Value in Excel

Published On: Last updated: Joseph Mburu 4 min read
Z Critical Value in Excel

After performing a z-test, the next step is deciding whether to reject the null hypothesis. This decision is based on the z critical value. If the absolute value of your z-test statistic exceeds the z critical value, you reject the null hypothesis. Otherwise, you fail to reject the null hypothesis. While you can find the z critical value using a standard normal table or an online z-critical calculator, Excel offers a quick and easy way to get it. In this article, we’ll guide you on how to find the z critical value using Excel.

How to Find Z Critical Value in Excel

Finding the z critical value in Excel is actually pretty easy with the NORM.S.INV() function. You only need to know the significance level (α) and the type of test (two-tailed, left-tailed, or right-tailed) you’re performing. In this section, we’ll show you how to get the z-critical value in Excel for each type of test.

1. Right-Tailed Test (>)

Suppose you’re performing a right-sided test. To find the z-critical value for your test in Excel, follow these steps:

  1. Identify your significance level (α)
  2. Enter the formula: =NORM.S.INV(1 - α) in the cell where you want the critical value to appear
  3. Press Enter to get the critical value.

Example 1: Find the right-tailed Z critical value for α = 0.05.

To find this right-tailed critical value, we simply type the formula =NORM.S.INV(1 - 0.05) in excel cell. Once you click enter, we get the right-sided z critical value as 1.645 (See Figure 1).

Right-tailed z-critical value using excel
Figure 1. Right-Tailed Excel Solution

2. Left-Tailed Test (<)

Suppose now you’re conducting a left-tailed z test. You can easily find the left-sided z-critical value using Excel using these simple steps:

  1. Identify your significance level (α).
  2. Enter the formula: =NORM.S.INV(α) in a cell where you want the critical value to appear.
  3. Press Enter to get the critical value.

Example 2: Find the left-tailed Z critical value for α = 0.10

To find the left-sided z-critical value for α = 0.10, simply type the formula =NORM.S.INV(0.10) in a cell where you want the critical value to appear and click Enter. The resulting left-tailed critical value will be -1.2816 (See Figure 2).

Left-tailed z critical value using Excel
Figure 2. Left-Tailed Excel Solution

3. Two-Tailed Test (≠)

If you’re performing a two-sided z-test, you can easily find the correct z-critical value using Excel by following these simple steps:

  1. Identify the significance level (α)
  2. Enter the formula: =NORM.S.INV(1 - α/2)
  3. Press Enter to get the Z critical value.

Example 3: Find the two-tailed Z critical value for 95% confidence level.

If we want to be 95% confidence, then the significance level, α = 1-.95 =0.05

Thus, to compute the two-sided critical value using Excel, type the formula =NORM.S.INV(1 - 0.05/2) and hit the Enter key. The results will be 1.96 (See Figure 3).

Two-tailed z critical value excel solution
Figure 3. Two-Tailed Excel Solution

Want to learn how to find z-critical value manually? Check out our comprehensive guide on how to find Z critical value from Z tables.

Common Mistakes to Avoid

When calculating Z critical values in Excel, beginners often make simple mistakes. Avoid these to get accurate results:

  • Confusing confidence level with alpha (α): Remember that α = 1 – confidence level. Using the confidence level directly in the formula will give incorrect values.
  • Forgetting α/2 in two-tailed tests: In a two-tailed test, you must divide alpha by 2 before using it in the formula.
  • Mixing up left-tail and right-tail tests: Using the wrong formula for the test direction will reverse the sign of your Z critical value.
  • Using the wrong function: Use NORM.S.INV() for standard Z critical values. Avoid using NORM.INV(), which is for custom distributions.
  • Entering percentages instead of decimals: Excel formulas require probabilities in decimal form. For example, enter 0.05 instead of 5%.
About the Author
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Joseph is an experienced Statistician and Data Analyst with over six years of hands-on work in applied statistics, data science, and quantitative research. He holds advanced degrees in Applied Statistics and Data Analytics, reflecting strong technical and academic expertise. Joseph is the founder of Stat Study Hub, a platform designed... Read more