Maths-
General
Easy
Question
If the lines of regression are 3x+12y=19 and 3y+9x=46 then
will be
- 0.289
- – 0.289
- 0.209
- None of these
The correct answer is: – 0.289
.
Related Questions to study
maths-
If regression coefficient of y on x is
and that of x on y is
and the acute angle between the two lines is
, then the value of
is
If regression coefficient of y on x is
and that of x on y is
and the acute angle between the two lines is
, then the value of
is
maths-General
maths-
The coefficient of correlation for the following data will be
![](data:image/png;base64,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)
The coefficient of correlation for the following data will be
![](data:image/png;base64,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)
maths-General
maths-
For the following data
![](https://mycourses.turito.com/tokenpluginfile.php/c161933dbfaab094c54655ab71e9b8f0/1/question/questiontext/503587/1/975057/Picture22.png)
the value of r will be
For the following data
![](https://mycourses.turito.com/tokenpluginfile.php/c161933dbfaab094c54655ab71e9b8f0/1/question/questiontext/503587/1/975057/Picture22.png)
the value of r will be
maths-General
maths-
The coefficient of correlation for the following will be approximately
![](data:image/png;base64,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)
The coefficient of correlation for the following will be approximately
![](data:image/png;base64,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)
maths-General
maths-
If correlation between x and y is r, then between y and x correlation will be
If correlation between x and y is r, then between y and x correlation will be
maths-General
maths-
If r=-0.97, then
If r=-0.97, then
maths-General
maths-
If r=0.2, then linear correlation will be necessarily
If r=0.2, then linear correlation will be necessarily
maths-General
maths-
Coefficient of correlation between x and y for the following data will be approximately
![](data:image/png;base64,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)
Coefficient of correlation between x and y for the following data will be approximately
![](data:image/png;base64,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)
maths-General
maths-
Coefficient of correlation from the following data will be
![](data:image/png;base64,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)
Coefficient of correlation from the following data will be
![](data:image/png;base64,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)
maths-General
maths-
Coefficient of correlation between x and y for the following data will be
![](data:image/png;base64,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)
Coefficient of correlation between x and y for the following data will be
![](data:image/png;base64,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)
maths-General
maths-
Karl Pearson's correlation coefficient between x and y for the following data will be approximately
![](data:image/png;base64,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)
Karl Pearson's correlation coefficient between x and y for the following data will be approximately
![](data:image/png;base64,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)
maths-General
maths-
Karl Pearson's coefficient of correlation between the marks in English and Mathematics by ten students will be
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)
Karl Pearson's coefficient of correlation between the marks in English and Mathematics by ten students will be
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)
maths-General
maths-
The coefficients of correlation between the heights (in inches) of fathers and sons from the following data will be
![](data:image/png;base64,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)
The coefficients of correlation between the heights (in inches) of fathers and sons from the following data will be
![](data:image/png;base64,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)
maths-General
maths-
Karl Pearson's coefficient of rank correlation between the ranks obtained by ten students in Mathematics and Chemistry in a class test as given below is
![](data:image/png;base64,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)
Karl Pearson's coefficient of rank correlation between the ranks obtained by ten students in Mathematics and Chemistry in a class test as given below is
![](data:image/png;base64,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)
maths-General
maths-
Karl Pearson's coefficient of correlation between x and y for the following data is
![](data:image/png;base64,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)
Karl Pearson's coefficient of correlation between x and y for the following data is
![](data:image/png;base64,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)
maths-General