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There is a very high inverse relationship between measures of ‘Overweight’ and ‘life expectancy’. Which one of the following value of the coefficient of correlation is consistent with the statement ?

There is a very high inverse relationship between measures of ‘Overweight’ and ‘life expectancy’. Which one of the following value of the coefficient of correlation is consistent with the statement ? Correct Answer -0.80

Negative correlation:

  1. The negative correlation indicates that as the values of one variable increase the values on another variable decrease.
  2. Similarly, as the values on one variable decrease the values on the other variable increase.
  3. It means that both the variables move in opposite directions.
  4. For example, as weight increases, life expectancy decreases due to problems like cholesterol, blood pressure, heart blockages, etc. In statistics, a perfect negative correlation is represented by the value -1. 

Since there is a very high inverse relationship, the value of the coefficient of correlation will be - 0.80.

Thus, option 4 is the correct answer.

Related Questions

There is a very high inverse relationship between measures of 'overweight' and 'life expectancy'. Which one of the following value of the coefficient of correlation is consistent with the statement?
Which of the following statements relating to correlation and reegression are true?
1. The coefficient of correlation is independent of change of origin and scale
2. The coefficient of correlation between the two variables is the arithmetic average of the two regression coefficients
3. The probable error of the coefficient correlation is 0.6745 times of its standard error
4. Coefficient of correlation multiplied by the ratio between the standard deviations of the two variables denotes the slope of the regression line
Select the correct answer:
Which of the following statements are true? a. The correlation coefficient is dependent on the choice of both origin and scale observations. b. The correlation coefficient is dependent on the units of measurements. c. The coefficient of correlation is the square root of the coefficient of determination. d. The zero value of the correlation coefficient cannot estimate the value of the dependent variable.
Which of the following statements are true?
1. The coefficient of rank correlation has the same limits as the Karl Pearson's coefficient of correlation.
2. The coefficient of correlation is independent of the change of origin but not of scale.
3. The covariance between $$X$$ and $$Y$$ is defined as $$\frac{{\sum {xy} }}{n}$$ where, $$x = \left( {X - \overline X } \right),y = \left( {Y - \overline Y } \right)$$      and $$n = $$ no. of paired observations.
4. $${b_{xy}}$$ is called regression coefficient of $$X$$ variable on $$Y$$ variable.
5. If $${b_{xy}}$$ is 0.4 and $${b_{yx}}$$ is 1.6, coefficient of determination would be 0.8.
Select the correct answer:
Statement I The product of coefficient of correlation, standard deviation of variable 'X' and Standard deviation of variable 'Y' gives the measure of covariance between X and Y variables.
Statement II The product of coefficient of correlation between X and Y variables and the ratio between standard deviation of X variable to standard deviation of Y variable measures the slope of the regression line of X on Y variable.
Which of the following statements are correct?
1. Correlation analysis helps in determining the relationship between two or more variables. It does not tell us anything about the cause and effect relationship.
2. The ratio of explained variation to the total variation is called the coefficient of correlation.
3. Pearsonian coefficient always assumes linear relationship, and is unduly effected by the extreme items.
The . . . . . . . . error of correlation is an amount which if added to and subtracted from the average correlation coefficient produces amounts within which the chances are even that a coefficient of correlation from a series error selected at random will fall.
Which of the following statements is false?  1. When value of correlation coefficient is one, the two regression lines coincide 2. The regression coefficients are independent of the change of origin and of scale 3. The sign of the regression coefficients are always the same 4. The square of the coefficient of correlation is called coefficient of determination 
An investigator obtained a correlation coefficient of +0.65 between two variables. The other investigator obtained a correlation coefficient of -0.65 between the same variables. Which of the two values indicates a higher degree of relationship?
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