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Data can be correlated (meaning there is an indication of a relationship) either positively or negatively. The datasets of two variables (x,y) which have a negative correlations, when plotted, will show a negative trend, that means with increasing values of x, there will be, generally, decreasing values of y. An example of negative correlation, would be the more hours someone exercises, the less they weigh, if weight loss is measured as a negative number and weight gain as a positive number. In this case x= hours exercised, y = final weight - original weight. For presentation purposes, we frequently define our variable to show positive correlations. As per the above example, I could have defined y = original weight - final weight, which would show a positive correlation and plot as an upward trend. It would not change the absolute value of correlation just the sign. You may check wikipedia under correlation to get more understanding.

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A positive value for a correlation indicates?

A positive value for a correlation indicates a positive correlation; e.g. it has a positive slope.


What does r value represent?

The r value, or correlation coefficient, quantifies the strength and direction of a linear relationship between two variables. Its value ranges from -1 to 1, where -1 indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 signifies no correlation. A higher absolute value of r indicates a stronger relationship, while the sign indicates the nature of the relationship.


What indicates the magnitude of a correlation coefficient?

The magnitude of a correlation coefficient, which ranges from -1 to 1, indicates the strength of the relationship between two variables. A value close to 1 signifies a strong positive correlation, meaning that as one variable increases, the other tends to increase as well. Conversely, a value close to -1 indicates a strong negative correlation, where an increase in one variable corresponds to a decrease in the other. A value around 0 suggests little to no correlation between the variables.


When are is close to -1 does it indicate a weak negative correlation?

No, it indicates an extremely strong positive correlation.


Is the slope of a line positive when doing linear regression if the correlation coefficient is negative?

No, the slope of a line in linear regression cannot be positive if the correlation coefficient is negative. The correlation coefficient measures the strength and direction of a linear relationship between two variables; a negative value indicates that as one variable increases, the other decreases. Consequently, a negative correlation will result in a negative slope for the regression line.

Related Questions

A positive value for a correlation indicates?

A positive value for a correlation indicates a positive correlation; e.g. it has a positive slope.


What does r value represent?

The r value, or correlation coefficient, quantifies the strength and direction of a linear relationship between two variables. Its value ranges from -1 to 1, where -1 indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 signifies no correlation. A higher absolute value of r indicates a stronger relationship, while the sign indicates the nature of the relationship.


What indicates the magnitude of a correlation coefficient?

The magnitude of a correlation coefficient, which ranges from -1 to 1, indicates the strength of the relationship between two variables. A value close to 1 signifies a strong positive correlation, meaning that as one variable increases, the other tends to increase as well. Conversely, a value close to -1 indicates a strong negative correlation, where an increase in one variable corresponds to a decrease in the other. A value around 0 suggests little to no correlation between the variables.


Define correlation coefficients?

Correlation coefficients measure the strength and direction of a relationship between two variables. They range from -1 to 1: a value of 1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation. They are commonly used in statistics to quantify the relationship between variables.


When are is close to -1 does it indicate a weak negative correlation?

No, it indicates an extremely strong positive correlation.


What is the acceptable range of correlation coefficient?

The correlation coefficient, typically denoted as "r," ranges from -1 to +1. A value of +1 indicates a perfect positive correlation, -1 indicates a perfect negative correlation, and 0 indicates no correlation. Generally, values between 0.1 and 0.3 suggest a weak correlation, 0.3 to 0.5 indicate a moderate correlation, and above 0.5 show a strong correlation. The interpretation may vary depending on the context and the specific fields of study.


What does a correlation coefficient of zero indicates?

A coefficient of zero means there is no correlation between two variables. A coefficient of -1 indicates strong negative correlation, while +1 suggests strong positive correlation.


Is the slope of a line positive when doing linear regression if the correlation coefficient is negative?

No, the slope of a line in linear regression cannot be positive if the correlation coefficient is negative. The correlation coefficient measures the strength and direction of a linear relationship between two variables; a negative value indicates that as one variable increases, the other decreases. Consequently, a negative correlation will result in a negative slope for the regression line.


What is the range of correlation coefficient and what does its value tell?

The product-moment correlation coefficient or PMCC should have a value between -1 and 1. A positive value shows a positive linear correlation, and a negative value shows a negative linear correlation. At zero, there is no linear correlation, and the correlation becomes stronger as the value moves further from 0.


What does it mean for variables to show correlation?

A positive correlation coefficient means that as the value of one variable increases, the value of the other variable increases; as one decreases the other decreases. A negative correlation coefficient indicates that as one variable increases, the other decreases, and vice-versa.


What does the value of a correlation coefficent reflects?

A correlation reflects the strength of the relationship between two variables. A correlation doesn't reflect causation, but merely that two phenomena are present at the same time. The closer the value is to 1, the stronger the relationship between two variables is. This value can be positive or negative. A negative value merely indicates that, as the values on one variable increase, the values on the second variable decrease. A positive correlation indicates that both values will increase or decrease together.


What is the process of correlation?

Correlation is a statistical measure that indicates the extent to which two or more variables fluctuate together. A positive correlation indicates the extent to which those variables increase or decrease in parallel; a negative correlation indicates the extent to which one variable increases as the other decreases.