Today, we will learn how to use the qchisq function to calculate the p-values of a chi-squared statistic in the R programming language. See the syntax and example below to understand it better.

**What is the pchisq Function in R?**

In R, the pchisq function is used to compute the probability that a random variable, which follows a chi-squared distribution, will be less than or equal to a given value.

Below is the basic syntax for using the pchisq function in R

**pchisq Function in R: The Syntax**

Parameters

**q:**The value for which you want to compute the probability.**df:**is the degrees of freedom.**lower.tail:**is a logical value that determines whether to calculate the probability that the random variable is more significant than q (FALSE) or less than q (TRUE) (FALSE).

**How to use the pchisq Function in R?**

Now, we will use the pchisq function in R to compute the probability that a chi-squared random variable with 5 degrees of freedom is less than or equal to 4 as follows:

# Calculate the p-value for the Chi-Square statistic res <- pchisq(q = 4, df = 5) # View a result res

Output

`[1] 0.450584`

If you want to calculate the probability to the right of **q **in the Chi-Square distribution, see the code example below

# Calculate the p-value for the Chi-Square statistic res <- pchisq(q = 4, df = 5, lower.tail = FALSE) # View a result res

Output

`[1] 0.549416`

The pchisq function can also be used to get the p-values for a vector of test statistics with the q arguments. For instance:

First, we will create a vector as follows

# Create a vector set.seed(100) x <- sample(10) # View a vector x

Output

`[1] 10 7 6 3 1 2 5 9 4 8`

Then, we can use the pchisq function to calculate p-values for the vector above. Check out the code example below

# Create a vector set.seed(100) x <- sample(10) # Calculate the p-value for the Chi-Squared statistic res <- pchisq(x, df = 5) res

Output

```
[1] 0.92476475 0.77935969 0.69378108 0.30001416 0.03743423 0.15085496
[7] 0.58411981 0.89093584 0.45058405 0.84376437
```

The output above can be seen by charting it as shown below.

# Create a vector set.seed(100) x <- sample(10) # Calculate the p-value for the Chi-Squared statistic res <- pchisq(x, df = 5) # Plot a chart plot(res, type = "l", main = "The Chi-Squared", xlab = "The X-Value", ylab = "The P-value" )

Output

**Summary**

In conclusion, this article helps you know how to use the pchisq function in r to calculate Chi-Squared statistics. If you have any questions, do write a comment below.

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