Question

For this week's discussion I want you to find a study that uses linear regression and a line of best fit. What is the Correlation Coefficient? What conclusions can you make about the data? Is there a correlation and how strong is it? Post your study and your findings and then read your classmates studies and findings; respond whether you agree or disagree with their findings.

Answer 1

linear regression attempts to model the relationship between two variables by fitting a linear equation to observe a data. one variable is consider to be an explanatory variable and other is consider to be a dependent variable. the most common method for fitting a regression line is the method of least- squares.the method calculate the best fitting line for the observed data by minimizing the sum of the square of the vertical deviation from each data point to the line.in simple linear regression predict scores on a second variables.the variable we are predicting is called the criterion variable.known as Y.

the variable we are bashing our predictions on is called the predictor variable is refereed to as X. when there is only predictor variable. the prediction method is called simple regression. linear regression consist of finding the best fitting straight line through the points.the best fitting line is called regression line. correlation coefficient : it is a statistical measure the strength of the relation between the relative movements of two variable. the value ranges between 1.0 to -1.0 A. a calculated number greater than 1.0 or less than -1.0 means that there was an error in the correlation measurements. A correlation of -1.0 shows an ideal indirect correlation . while a correlation of 1.0 shows a positive correlation.A correlation of 0.0 shows no relationship between the movement of the two variables.