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**Table of Content**

For a given set of values, the t statistic calculator calculates the T statistic and the corresponding p-value, allowing you to determine the statistical significance of the results. In this way, you can determine the difference between the mean of the two groups.

T-Test Statistics is the metric that is used to quantify the relation between a sample and its population. This t-test statistics assesses the hypotheses regarding the population mean.

The t-statistics determines that the results rejected or support the null hypothesis and it takes into account the probability of results occurring by chance.Â The t-statistic is a key part of the Student’s t-test, which compares the average of a sample with the average of the whole population.

\( t=\frac{\bar{x}-\mu}{s \sqrt{n}}\)

Where:

**XÌ„ = sample mean**

**Î¼ = population mean**

**n = sample size**

**s = standard deviation**

In the case of small sample sizes or uncertain population standard deviation, the t statistics is commonly used in place of the z-statistics.

The t statistic is evaluated by comparing the difference between the sample means to the variability within the samples, and the t statistics calculator automates this calculation for ease and accuracy.

If a sample of learners has different average heights from the known population average height is 65 inches. How to calculate T value for one sample in which the mean height is 67 inches and the sample standard deviation is 3 inches?

**Given Values:**

- Population Mean (Î¼) = 65 inches
- Sample Mean xÌ„ = 67 inches
- Sample Size (n) = 25
- Sample Standard Deviation (s) = 3 inches

\(=\dfrac{\bar{x} – Î¼}{s \sqrt{n}}\)

\(=\dfrac{67 – 65}{3 \sqrt{25}}\)

\(=\dfrac{2}{3 * 5}\)

\(=\dfrac{2}{15}\)

\(=0.13\)

It is a simple process to use the t score calculator to interpret the statistical significance of your data. So have a look at the points below:

**Inputs:**

- (xÌ„) Sample mean
- (Î¼) Population mean
- Sample size
- (s) Sample standard deviation

**Outputs:**

- T statistics
- Complete solution with steps

In hypothesis testing, t-score is used to compare various sets of data or multiple values within the same set. It measures how similar the data is in terms of standard deviations. So;

- A low t-score shows that the groups have similarities between the two sample sets.
- A large t-score shows that the groups are different between the two sample sets.