Low Degree of Positive Correlation : Students who have understood these above-mentioned graphs and their representations can easily understand that in the case of a low degree of correlation, be it positive or negative, these plotted points are scattered.Īmong the importance of scatter diagrams, a low degree of correlation is also a vital analysis since it suggests incoherence. Representing the scatter diagram meaning and values, in the event of a high degree of negative correlation, every plotted point forms a band that falls from top left corner to the right bottom corner. High Degree of Negative Correlation : Much like the 2 perfect correlations, high degrees of positive and negative correlation are reciprocal of each other. Typically, these graphs look like the representation below. This representation typically forms a band-like structure which is rising from the bottom left corner towards the top right corner. High Degree of Positive Correlation : If a scatter diagram represents a high degree of positive correlation then all its plotted points are roughly along a straight line, even though they do not clearly create a line. Students can see its representation in this diagram given below. However, unlike in the case of positive correlation, here this plotted point creates a line which is approaching from the top left corner towards the bottom right corner. Here, every plotted point lies on a straight line without exception too. Perfect Negative Correlation: Among scatter diagram examples, a perfect negative correlation is reciprocal of the previous type. This can be seen in the representation below. Perfect Positive Correlation : A scatter diagram is known to have a perfect positive correlation if all the plotted points are on a straight line when represented on a graph.Īdditionally, students must also note that all these points form a straight line which is rising from its lower-left corner to the top right corner. Students Should Note the Relevant Graphs Properly Notably, though there can be many representations, each of which suggests different types of correlation, the most common and vital ones are explained below. While understanding its various types, it is important to describe the scatter diagram with examples for a better understanding of the students. Notably, scatter diagram correlation is a quantitative measure of random variables and their association with each other. Consequently, students can also calculate the correlation of coefficient of this given data using their plotted representation.

Correspondingly, all these points are plotted on the graph and their totality is termed as a scatter diagram.Īfter plotting all these points on a graph, the generated profiles of these scatter plots are used to draw an extrapolation. These variables can be taken as independent variables, though this makes the second variable dependent on this former one. Two variables involved in a study are represented on the X and Y axis. Scatter diagrams in statistics and commerce are a vital tool that requires precision since their analysis depends on such representations. Students must be very particular while plotting such graphs. The study of such a graphical representation involving two variables and using such a diagram is known as scatter diagram analysis. These two variables are plotted along the X and Y axis on a two-dimensional graph and the pattern represents the association between these given variables. The Scatter diagram method is a simple representation that is popularly used in commerce and statistics to find the correlation between two variables.

Scatter gram