There is zero correlation between the shoe size of a person and the number of movies he/she has watched, i.e., one can not analyse the number of movies a person watches per year by knowing his/her shoe size. Shoe Size and the Number of Movies Watched There is zero correlation between the amount of tea a person drinks and his/her intelligence level, i.e., one can not assume the intelligence level of a person by knowing the amount of tea he/she drinks. There is zero correlation between the height of a person and the salary he/she earn, i.e., if you know the height of a person you can not estimate the income of that person. There is zero correlation between the weight of the student and his/her score in the exams, i.e., one can not analyse the scores a person will obtain in any exam by knowing the weight of that person. Here are some examples of the zero correlation, Weight and Exam Scores The following image represents the Scattergram of the zero correlation. If the value of r is near to the +1 and -1, it indicates that there exists a strong linear relation in the given variables, and if the value is near 0, it indicates a weak relationship. The correlation coefficient measures direction and the strength between the two variables. A zero correlation is represented by the ‘r=0.’ Where ‘r’ is the correlation coefficient. For example, there does not exist the relation between the packets of chips you ate and your marks in the last exam. Let’s discuss them in detail with real-life examples of correlation.Ī zero correlation indicates that there does not exist any relationship between the two variables. There is three possible outcomes of the correlation study, i.e., the positive correlation, the negative correlation, and the zero correlation. The points on this plot represent the different measurements and a trend line can be drawn from these measurements if the trend line is not clear, it means weak correlation (r is near to zero), and if the trend line is clearly visible it means strong correlation (r is near to 1). It is a type of graph that clearly represents the association between the two variables, where one variable is represented on the horizontal axis, and the other on the vertical axis. The data obtained through the correlation studies are represented on the ‘scattergram,’ which is also known as the scatter diagram, scatter chart, or scatter plot. Correlational studies are widely used in psychology researches as various psychological factors like perception, attitude, motivation and so on are difficult to control, hence the relationship between these factors or variables can be drawn with the help of the correlation studies. The researcher need not perform any experiment, and he/she is only required to collect the data by observing the relationships among the given variable, and then making the accurate interference out of the collected data. While conducting various researches, it is difficult to do certain experiments in laboratory settings, in this case, correlation studies are conducted. In other words, it measures the degree or extent to which two different entities are related to each other. Time Spent Watching T.V and Score in the ExamsĬorrelation is the statistical association between the two variables.Sales of the Apartment and the high Cost.Ice Cream Sales and the Weather Temperature.Boiling Point of the Water with the Increase in the Impurities.Improvement in the Health and the Medical Dose.Time Spent in Meetings and Value of the Person in the Company.Sale of Apartment and the Infrastructure.Shoe Size and the Number of Movies Watched.
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