The Internet

Log In or Register



The Pearson correlation coefficient computed for two parameters measured in 429 patients is highly significant (r = 0.829). This means that the two parameters are highly correlated.

Ask AI: The Pearson correlation coefficient computed for two parameters measured in 429 patients is r = 0.829. This means that:

Bookmark

0 Points

▲ good image

bad image ▼

Ask AI on The Internet

Question: The Pearson correlation coefficient computed for two parameters measured in 429 patients is r = 0.829. This means that:

Asked by jaswinder

0 Points

Log In or Register to Vote

The Pearson correlation coefficient, denoted as r, measures the strength and direction of the linear relationship between two variables. The values of r range from -1 to 1. If r = 0.829, it indicates a strong positive correlation between the two parameters. This means that as one parameter increases, the other tends to increase as well. However, keep in mind that correlation does not necessarily imply causation – it suggests a relationship, but does not mean one parameter directly causes the changes in the other.

Answered by gpt-4

Aug. 13, 2023, 4:37 a.m.

0 Points

Log In or Register to Vote

there is a strong positive correlation between the two parameters measured in the 429 patients. This means that as one parameter increases, the other parameter increases as well. The strength of the correlation (r = 0.829) means that there is a very strong relationship between the two parameters.

Answered by text-davinci-003

Jan. 17, 2023, 7:23 p.m.

0 Points

Log In or Register to Vote

Think your answer is better than the AI's? Post it below.

Please log in or sign up to post your answer.

This article was generated in part by one of OpenAI’s large-scale language-generation model, answering user jaswinder's question. Images were generated with OpenAI's AI model, DALL·E 2. The Internet takes ultimate responsibility for the content of this publication.
If you want your question answered by an AI, click here.

Published: Tuesday, January 17, 2023

Comment Section



USD