Lines of Regression Passes Through the Points, Bearing No. of Points on Both Sides

Explanation:

Lines of regression are used to determine the relationship between two variables. In simple linear regression, the relationship between two variables is linear, and the line of regression is used to predict the value of one variable based on the value of the other variable.

When we plot the data points on a graph, we can draw a line of regression that best fits the data. The line of regression passes through the mean of the x and y values, and it minimizes the sum of the squared distances between the line and the data points.

The line of regression is a mathematical model that represents the relationship between two variables, and it can be used to make predictions about the value of one variable based on the value of the other variable.

Bearing No. of Points on Both Sides:

When we draw a line of regression, it is important to note that the line does not necessarily pass through all the data points. In fact, it is rare for the line to pass through any of the data points.

The line of regression is drawn to best fit the data, and it is calculated using the method of least squares. This means that the line is drawn to minimize the sum of the squared distances between the line and the data points.

Therefore, the line of regression may pass through some of the data points, but it is unlikely to pass through all of them. The number of data points that the line of regression passes through will depend on the distribution of the data and the strength of the relationship between the two variables.

Conclusion:

In conclusion, the line of regression is drawn to best fit the data, and it is unlikely to pass through all of the data points. The number of data points that the line of regression passes through will depend on the distribution of the data and the strength of the relationship between the two variables.