You can say that the correlation is positive if and only if the slope is positive. The correlation is zero if and only if the slope is zero. And the correlation is negative if and only if the slope is negative. On the other hand, slope does change when your measurement units change, while correlation does not change. (For example, the correlation between height in inches and weight in pounds will be the same as the correlation between height in centimeters and weight in kilograms, as long as both sets of measurements were taken on the same observations.)
Correlation determines relationship between two variables. For example changes in one variable influence another variable, we can say that there is a correlation between the two variables. For example, we can say that there exists a correlation between the number of hours spent on reading and preparation and the scores obtained in the examination. One can infer that higher the amount of time spent on preparation may result in better performance in examination leading to higher scores. Hence the above is a case of positive correlation. If an increase in independent variable leads to an increase in dependent variable, it is a case of positive correlation. On the other hand if an increase in independent variable leads to a reduction in dependent variable, it is a case of negative correlation. An example for negative correlation could be the relationship between the age advancement and resistance to diseases. As age advances, resistance to disease reduces.
good correlation
The slope of height vs. time squared graph equals (g) - acceleration due to gravity divided by two. In symbols m = g/2, where m is the slope and g is the acceleration due to gravity.
Things may be correlated without causal relationship or conversely. Consider the Modulus function - that is the value of a number without regard to its sign. Over any domain (-a,a), there is a very strict relationship between x and mod(x), but their correlation is 0. Conversely, I expect that there is a good correlation between my age and the number of TV sets in the world. That is not to say that my getting older is producing more TVs or that TV production is causing me to age. Simply that both of them are correlated to a third variable - time. There can be correlation without such a third variable but, offhand, I cannot think of an example.
In science, positive correlation is a general positive slope in something. Often times this is represented with a graph, using many points of data, for instance, height vs age would be a positive correlation. The meaning of positive correlation in both science and math are very, very similar. Only the scenarios they are used in differ.
Positive Correlation- Age - Amount of medical conditions Negative Correlation- Television Watching- Grades No Correlation- Height of a person- Number of shoes they own Hope this was helpful!
there is none.
no correlation.
No, the height of an NBA player in relationship to his shoe size does not represent a negative correlation. The two actually represent a positive correlation. As the NBA player increases in size, so will his shoe size.
You can say that the correlation is positive if and only if the slope is positive. The correlation is zero if and only if the slope is zero. And the correlation is negative if and only if the slope is negative. On the other hand, slope does change when your measurement units change, while correlation does not change. (For example, the correlation between height in inches and weight in pounds will be the same as the correlation between height in centimeters and weight in kilograms, as long as both sets of measurements were taken on the same observations.)
the age of adults and the amount of sleep they get (:
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There are three types of correlation: positive, negative, and none (no correlation).Positive Correlation: as one variable increases so does the other. Height and shoe size are an example; as one's height increases so does the shoe size.Negative Correlation: as one variable increases, the other decreases. Time spent studying and time spent on video games are negatively correlated; as the your time studying increases, time spent on video games decreases.No Correlation: there is no apparent relationship between the variables. Video game scores and shoe size appear to have no correlation; as one increases, the other has no effect. A No Correlation graph would show this.
There is a reasonably strong positive correlation.
There are three types of correlation: positive, negative, and none (no correlation).Positive Correlation: as one variable increases so does the other. Height and shoe size are an example; as one's height increases so does the shoe size.Negative Correlation: as one variable increases, the other decreases. Time spent studying and time spent on video games are negatively correlated; as the your time studying increases, time spent on video games decreases.No Correlation: there is no apparent relationship between the variables. Video game scores and shoe size appear to have no correlation; as one increases, the other has no effect. A No Correlation graph would show this.
A woman's period does not affect her height. Her height is affected by the genetics of her family which will determine how tall she grows.