pchisq Function In R: The Chi-Square Statistic

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.

Have a great day!

Scott Miller

Hi, guys! My name’s Scott Miller. My current job is a software developer and I have shared a lot of quality articles about Javascript, C, C++, C#, Python, PHP, R, Java programming languages. I’m hoping they can assist you.

Name of the university: HCMUS
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