# T-Test

**Use:** To **compare** **means of two groups** to determine if they are significantly different. To check if there is a statistically significant difference between the means of two groups. It's commonly used when you have a small sample size and want to understand if the means of two populations are significantly different.

**Example:** A pharmaceutical company wants to test if a new drug is more effective than a placebo in reducing blood pressure. They compare the average blood pressure measurements before and after treatment for both groups.

<figure><img src="https://2063668468-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F9RcwqzNNsjo496JLJ2Ob%2Fuploads%2FL11YySo7FnfoyUiZbyAU%2Fimage.png?alt=media&#x26;token=d6d6a831-a06a-4ab8-9c88-ffbc20e41558" alt=""><figcaption></figcaption></figure>

{% hint style="info" %}
**Column Requirement:** Continuous data is required for two independent groups.
{% endhint %}

**Steps:**

1. Select two continuous columns, each representing a group (e.g., blood pressure before and after treatment).
2. Ensure that the data distribution is approximately normal or at least not highly skewed.
3. Perform the t-test after selecting the columns using the Test button.
4. Interpret the results and draw conclusions accordingly.