The number of pounds increases as the number of calories consumed increases.
Positive correlation.Positive correlation.Positive correlation.Positive correlation.
It is easy to find the correlation. First you see how far apart the dots are. if they are going UP like this / <---- it means its a positive correlation. if its like this \ <---- its a negative correlation. if its everywhere its a neutral (although they almost never do them in tests). To find out the strength is your opinion. If alot are grouped together almost making a line its a Strong correlation. Then you decide if its a Strong or Weak correlation depending on how close together the dots are. So put them together in a 1 mark question like::::it is a Strong Positive Correlation
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.
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.)
You can find examples by typing it in to Google. Weak positive correlation is a set of points on a graph that are loosely set around the line of best fit. The line will be positive rising up from left to right. A weak correlation can vary a lot as long as you can decipher which direction the data tends towards you have a correlation. If the points are close to the line of best fit you have a strong correlation and with a set of points perfectly lined up is perfect correlation. All three types can positive negative or perfect.
a strong negative correlation* * * * *No it is not. It is a very weak positive correlation.
No, it indicates an extremely strong positive correlation.
Demand and quantity sold is an example of positive correlation. As the number of people in demand of a product increases, the quantity sold of that product also increases.
A positive value for a correlation indicates a positive correlation; e.g. it has a positive slope.
A positive correlation.
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!
The number of pounds increases as the number of calories consumed increases.
Positive correlation = positive association Negative correlation = negative association
Positive correlation has a positive slope and negative correlation has a negative slope.
positive correlation-negative correlation and no correlation
yes