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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 else can I help you with?
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.
What is the difference between positve and negative correlation?
Positive correlation has a positive slope and negative correlation has a negative slope.
When a pair of variables have a positive correlation will the slope in the regression equation always be positive?
Yes
If the r-value or correlation coefficient of a data set is negative the coefficient of determination is negative?
The coefficient of determination, denoted as (R^2), is always a non-negative value, regardless of whether the correlation coefficient (r-value) is negative or positive. The value of (R^2) indicates the proportion of the variance in the dependent variable that can be explained by the independent variable(s). While a negative r-value signifies an inverse relationship between the variables, (R^2) will still be a positive number, ranging from 0 to 1. Thus, a negative r-value does not imply a negative coefficient of determination.
Is certain a negative connotation or positive correlation?
A positive correlation.
When doing linear regression if the correlation coefficient is positive the slope of the line is negative?
False.
Can A regression equation have a negative coefficient of correlation and a negative coefficient of determination?
It's not quite possible for the coefficient of determination to be negative at all, because of its definition as r2 (coefficient of correlation squared). The coefficient of determination is useful since tells us how accurate the regression line's predictions will be but it cannot tell us which direction the line is going since it will always be a positive quantity even if the correlation is negative. On the other hand, r (the coefficient of correlation) gives the strength and direction of the correlation but says nothing about the regression line equation. Both r and r2 are found similarly but they are typically used to tell us different things.
What does the sign of the correlation coefficient tell you about the association?
Positive correlation = positive association Negative correlation = negative association
Is 0.5 the strongest correlation coefficient?
No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).
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.
Will the correlation coefficient for these data points be positive or negative 24 47 512?
positive
What are the three ways to describe data in a scatter plot?
You can describe if there's any obvious correlation (like a positive or negative correlation), apparent outliers, and the corrlation coefficient, which is the "r" on your calculator when you do a regression model. The closer "r" is to either -1 or 1, the stronger that correlation is.
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.
When is the standard correlation coefficient positive?
Assume that you are correlating two variables x and y. If there is an increasing relationship between x and y, (that is , the graph of y=a+bx, slopes upward), the correlation coefficient is positive. Similarly, if there is a decreasing relationship, the correlation coefficient is negative. The correlation coefficient can assume values only between -1 and 1.
What is the maximum and minimum value of the correlation coefficient?
The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).
What shows a correlation which may be positive or negative between two sets of data?
I believe you are asking how to identify a positive or negative correlation between two variables, for which you have data. I'll call these variables x and y. Of course, you can always calculate the correlation coefficient, but you can see the correlation from a graph. An x-y graph that shows a positive trend (slope positive) indicates a positive correlation. An x-y graph that shows a negative trend (slope negative) indicates a negative correlation.
does The strength of the correlation between two variables depend on the sign of the coefficient of correlation?
No, it depends upon the size of the coefficient of correlation: the closer to ±1 the stronger the correlation.When the correlation coefficient is positive, one variable increases as the other increases; when negative one increases as the other decreases.
