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Critical Value Calculator

Perform hypothesis testing through our efficient critical value calculator

Perform hypothesis testing through our efficient critical value calculator

Critical Value Calculator

by Ahmad Sattar
Critical Value Calculator
Critical Value Calculator
Critical Value Calculator

What is it about?

Perform hypothesis testing through our efficient critical value calculator.

Critical Value Calculator

App Details

Version
1.0.1
Rating
NA
Size
24Mb
Genre
Utilities Productivity
Last updated
September 19, 2025
Release date
March 1, 2022
More info

App Screenshots

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Critical Value Calculator screenshot-1
Critical Value Calculator screenshot-2
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Critical Value Calculator screenshot-6

App Store Description

Perform hypothesis testing through our efficient critical value calculator.
Critical value calculator, a hands-on tool for statisticians, calculates t-value and z-value with a click. Single t-value calculator and z-value calculator are available for use yet, they do not suffice the needs of students. However, in this critical score calculator you can calculate both critical values.
Now you can get rid of tiresome practice of looking through hundreds of t- and z-value tables because critical value calculator calculates them in an instant.
How to perform calculations:
Calculate t-value
1. Specify the significance level in the given box.
2. Select degrees of freedom.
3. Calculate t-value
Calculate z-value
1. Enter the significance level in the input box.
2. calculate p-value
You can reset the critical value calculator by pressing “reset” button.

Basic definitions:
1. Critical value: It is the cut-off value of the graph generated by the test static and shows the region where test static does not lie. Critical value depends upon the significance level. T tells whether to accept of discard null-hypothesis.
2. Significance level: Significance level or statistical significance determines that the difference in population cannot be only associated with chance.
3. Null hypothesis: A hypothesis that describes no difference between two data. And if any difference is seen it appears only by chance. It is abbreviated as (Ho).
4. T-value: It is the calculated difference in the graph relative to the data.
5. Z-value: It is a cut-off point area under the standard distribution of data.

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