The <a target="_blank" href="https://www.almabetter.com/bytes/tutorials/applied-statistics/one-sample-t-and-z-test">one-sample t-test and z-test</a> are statistical hypothesis tests used to compare a sample mean to a known population mean.
<ul>
<li>One-sample t-test: Assesses whether the mean of a sample differs significantly from a known or hypothesized population mean when the population standard deviation is unknown. It calculates a t-statistic and compares it to a t-distribution to determine significance.
</li>
<li>Z-test: Similar to the t-test but applicable when the population standard deviation is known or when the sample size is large. It calculates a z-score and compares it to a standard normal distribution.
</li>
</ul>
Both tests help determine if observed differences are statistically significant.

The [one-sample t-test and z-test](https://www.almabetter.com/bytes/tutorials/applied-statistics/one-sample-t-and-z-test) are statistical hypothesis tests used to compare a sample mean to a known population mean.

* **One-sample t-test:** Assesses whether the mean of a sample differs significantly from a known or hypothesized population mean when the population standard deviation is unknown. It calculates a t-statistic and compares it to a t-distribution to determine significance.
    
* **Z-test:** Similar to the t-test but applicable when the population standard deviation is known or when the sample size is large. It calculates a z-score and compares it to a standard normal distribution.
    

Both tests help determine if observed differences are statistically significant.

One Sample T-Test and Z-Test