Perfect positive correlation example

Perfect Positive Correlation Example. Perfect correlation means both X and Y increase or decrease by the same degree. Thus one could expect a positive correlation between say the employment rate and auto stocks. An example would be the perfect negative correlation between a cars fuel efficiency X miles per gallon and the money spent per X miles the car is driven. A basic example of positive correlation is height and weighttaller people tend to be heavier and vice versa.

In some cases positive correlation exists because one variable influences the other. Perfect Correlation When there is a perfect linear relationship every change in the x variable is accompanied by a corresponding change in the y variable. An example of a perfect positive correlation is when comparing the number of people who go to see a movie and the total spent money on tickets when plotted on a graph it equals to 1. 10 20 30 40 50 b Example of perfect negative correlaion. If equal proportional changes are in the reverse direction. Or An example of perfect positive linear correlation.

An example would be the perfect negative correlation between a cars fuel efficiency X miles per gallon and the money spent per X miles the car is driven.

Weight it may look something like this. The example of the positive correlation includes calories burned by exercise where with the increase in the level of the exercise level of calories burned will also increase and the example of the negative correlation include the relationship between steel prices and the prices of shares of steel companies wherewith the increase in prices of steel share price of the steel companies will decrease. Ie Slope of 1 or -1. Correlation Analysis Example and Interpretation of Result perfect posive correlation r1 high positive correlation r09 low positive correlation05. This means that every time a number of people x go an amount of money y is spent without variation on the tickets. For example many economists have discovered that people tend to buy more cars and appliances during economic booms.