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Correlation coefficient value of 0.00 indicates two variables are not related?
Wiki User
∙ 13y ago
If the correlation coefficient is 0, then the two tings vary separately. They are not related.
Wiki User
∙ 13y ago
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When do you use Pearson's r?
See related link. As stated in the link: In probability theory and statistics, correlation (often measured as a correlation coefficient) indicates the strength and direction of a linear relationship between two random variables
Does a good correlation have to be positive?
No. If the correlation coefficient is close to 1 or -1, then the two variables have a high degree of statistical linear correlation. See the related link, particularly the graphs which illustrate correlation.
What is the meaning of zero correlation?
If variables have zero correlation, they do not have a linear relationship. Zero correlation shows that two things were not found to be related.
Is a correlation coefficient of -626 very strong?
A correlation coefficient has a range of -1 to 1. Any number outside of this range has been incorrectly calculated. I note that is you meant to ask - Is r= -0.626 is a very strong correlation coefficient? then the answer No, this value is not a strong indicator that a linear relationship exists. Please see related link. The diagrams showing x-y graphs and the correlation coefficients is a good way to gain a "feel" of the coefficients and strength of relationships.
What is correlation. What are the different types of correlation. Why is it important to determine correlation. What does it mean when it is said that two variables have no correlation?
A correlation is the relationship between two variables.Correlations are described as either weak or strong, and positive or negative, however there can be a perfect correlation between variables, or no correlation between variables.It is important to determine the correlation between variables in order to know if and how strongly one variable affects another variable (if one variable changes, how will the other variable react). This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction.-1 is less than or equal to r, r is less than or equal to +1if r= +1 or -1, there is a perfect relationshipif r= 0 there is no relationship between the variables, meaning that one variable does not affect the other variable and one variable could change without any change to the other variable.a value closer to + or - 1 demonstrates a strong relationship, while a value closer to 0 demonstrates a weak relationship.a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases.* * * * *Mostly a very good answer but ...It is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis.Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.
When do you use Pearson's r?
See related link. As stated in the link: In probability theory and statistics, correlation (often measured as a correlation coefficient) indicates the strength and direction of a linear relationship between two random variables
How does the time period or number of variables effect correlation coefficient?
The time period may not affect the correlation coefficient at all. If looking at the correlation between the mass and volume of steel objects, time is totally irrelevant. The effect of the number of variables depends on whether or not the extra variables are related to ANY of the variables in the equation.
Where is it not possible to use correlation?
It is not possible to use correlation when the two variables are not related at all. the corelation coefficient value that will be obtained will have no significance.
Does a good correlation have to be positive?
No. If the correlation coefficient is close to 1 or -1, then the two variables have a high degree of statistical linear correlation. See the related link, particularly the graphs which illustrate correlation.
How is coefficient of determination and coefficient of correlation is related?
coefficient of determination
What value or benefit would a researcher gain by calculating a correlation coeffcient rather than simply describing the relationship as a positive correlation or a negative correlation?
The correlation coefficient gives a measure of the degree to which changes in the variables are related. However, the relationship need not be causal.
What is correlation What are the different types of correlation Why is it important to determine correlation What does it mean when it is said that two variables have no correlation?
A correlation is the relationship between two or more variables. Correlations are described as either weak or strong, and positive or negative. There can be a perfect correlation between variables, or no correlation between variables. It is important to determine the correlation between variables in order to know if and how closely changes in one variable are reflected by changes in another variable. This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction. -1 ≤ r ≤ +1 if r= +1 or -1, there is a perfect correlation if r= 0 there is no correlation between the variables. a value closer to + or - 1 demonstrates a strong correlation, while a value closer to 0 demonstrates a weak correlation. a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases. However, it is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis. Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.
What is the meaning of zero correlation?
If variables have zero correlation, they do not have a linear relationship. Zero correlation shows that two things were not found to be related.
What is the strongest linear correlation?
The relationship between two random independently distributed variables is considered to be theoretically the weakest when the correlation coefficient is zero and theoretically the strongest when the correlation coefficient is one, indicating a positive relationship between two variables and negative one, indicating a negative relationationship between two variables. I state that this is a theoretical result as if variables are not random, independently distributed, then a high correlation coefficient can result. For example, let us say that we obtained the following data on age and frequency of accidents: Age 18 1 in 18 people have accidents in a year Age 25 1 in 25 people have accident in a year Age 30 1 in 30 people have accidents in a year Age 35 1 in 6 people have accidents. Age 40 1 in 400 people have accidents If I selectively calculated a correlation coefficient this data including only the three groups ages 18, 25 and 30, you can see I will have a correlation coefficient of 1, however the data was not a random sample of all ages. See related link.
What is the measure of how strongly two variables are related to one another?
correlation
Can coefficient of correlation be negative?
Yes. The range of r is from -1 to 1. See related link.
What is the difference between correlation analysis and?
Correlation analysis is a type of statistical analysis used to measure the strength of the relationship between two variables. It is used to determine whether there is a cause-and-effect relationship between two variables or if one of the variables is simply related to the other. It is usually expressed as a correlation coefficient a number between -1 and 1. A positive correlation coefficient means that the variables move in the same direction while a negative correlation coefficient means they move in opposite directions.Regression analysis is a type of statistical analysis used to predict the value of one variable based on the value of another. This type of analysis is used to determine the relationship between two or more variables and to determine the direction strength and form of the relationship. Regression analysis is useful for predicting future values of the dependent variable given a set of independent variables.Correlation Analysis is used to measure the strength of the relationship between two variables.Regression Analysis is used to predict the value of one variable based on the value of another.
