In a calculator, the **CDF function** stands for **Cumulative Distribution Function**. It is commonly used in statistics to evaluate the probability that a random variable \( X \) will take a value less than or equal to a specific value \( x \). 

Here's how it works:

- **CDF of a discrete random variable**: It sums up the probabilities of all outcomes less than or equal to \( x \).
  
- **CDF of a continuous random variable**: It integrates the probability density function (PDF) from \(-\infty\) to \( x \).

### Key Uses:
1. **Probability Calculations**: You can find the probability that a value falls within a certain range.
2. **Statistical Inference**: CDF is used in hypothesis testing, confidence intervals, and other statistical analyses.
3. **Modeling Distributions**: It's fundamental in understanding and working with various probability distributions.

### Example:
If you're using the CDF function for a normal distribution, inputting a value into the calculator will give you the probability that the random variable is less than or equal to that value.

### Would you like more details on CDF, or do you have any other questions?

Here are some related questions:
1. How does CDF differ from PDF in statistics?
2. How do you calculate CDF for a normal distribution manually?
3. What is the inverse CDF function, and how is it used?
4. Can you explain how CDF is used in statistical hypothesis testing?
5. What are some common distributions where CDF is frequently used?

**Tip**: When working with CDF on calculators, ensure you know which distribution you're dealing with, as different distributions have different CDF formulas.

Explore the CDF (Cumulative Distribution Function) function in calculators and its role in probability calculations and statistical inference. Learn how to use CDF for discrete and continuous random variables with practical examples.

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