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You have a positive correlation.

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13y ago
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1w ago

When variables in a correlation change simultaneously in the same direction, this indicates a positive correlation. This means that as one variable increases, the other variable also tends to increase. Positive correlations are typically represented by a correlation coefficient that is greater than zero.

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Q: When the variables in a correlation change simultaneously in the same direction?
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Does the units affect the correlation?

No. The units of the two variables in a correlation will not change the value of the correlation coefficient.


What is the implication of any correlation found between the variables?

Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.Correlation is a measure of the degree to which two variables change together. Positive correlation means that the variables increase together and decrease together. Negative correlation means that one variable increases when the other decreases.Correlation does not imply causality.


What does a correlation coefficient represent?

The correlation coefficient for two variables is a measure of the degree to which the variables change together. The correlation coefficient ranges between -1 and +1. At +1, the two variables are in perfect agreement in the sense that any increase in one is matched by an increase in the other. An increase of twice as much in the first is accompanied by double the increase in the second. A correlation coefficient of -1 indicates that the two variables are in perfect opposition. The changes in the two variables are similar to when the correlation coefficient is +1, but this time an increase in one variable is accompanied by a decrease in the other. A correlation coefficient near 0 indicates that the two variables do not move in harmony. An increase in one is as likely to be accompanied by an increase in the other variable as a decrease. It is very very important to remember that a correlation coefficient does not indicate causality.


What is the difference between correlation and experiment?

An experiment is when the researcher manipulates the independent variable and records its effect on the dependent variable whilst maintaining strict control over any extraneous variables. A correlation is a statistical relationship between two or more variables. The researcher makes a change in one of the variables to see what is affected.


How change of origin or scale effect value of co-efficient of co-relation?

The correlation coefficient is unaffected by change of origin or scale unless one of the sets of variables is multiplied by a negative term, in which case the correlation coefficient will become negative.


What does ''highly correlated'' mean?

Correlation is defined as the degree of relationship between two or more variables. It is also called the simple correlation. The degree of relationship between two or more variables is called multi correlation. when two or more variables are said to be higjly correlated it means that they have a strong relationship such that a given rise or fall in one variable will lead to a direct change in the other variable or variables. good examples of highly correlated variables are price and quantity, wage rate and out put, tax and income.


What is the correlation coefficient of -0.80 is found between factor A and factor B?

The correlation coefficient is a statistical measure of the extent to which two variables change. A correlation coefficient of -0.80 indicated that, on average, an increase of 1 unit in variable X is accompanied by a decrease of 0.8 units in variable Y. Note that correlation does not imply causation.


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.


What if a correlation coefficient of .721 was observed in a study examined relationship between parental sense of self efficacy and level of involvement in school activities what would you conclude?

You could conclude that there is moderate correlation between parental sense of self efficacy and level of involvement in school activities. There is moderate evidence that they change in the same direction (both increase or both decrease) but you may not conclude that one causes, or is caused by, the other.Both variables change


Why do historians need to distinguish between causation and correlation?

Correlation by itself is understood not to be sufficient to conclude causation. That two variables change together in a highly correlated way could mean that changes in both variables are being controlled or caused by something altogether different that has not yet come to light or that has not been considered as the cause.


What are variables that do not change in an experiment?

Variables that do not change in an experiment are independent variables.


The variables that do not change in an experiment are what?

Variables that do not change in an experiment are independent variables.