{"id":8204,"date":"2018-06-21T18:33:46","date_gmt":"2018-06-21T18:33:46","guid":{"rendered":"https:\/\/assignment.essayshark.com\/blog\/?p=8204"},"modified":"2022-01-05T09:44:43","modified_gmt":"2022-01-05T09:44:43","slug":"linear-regression-example","status":"publish","type":"post","link":"https:\/\/assignmentshark.com\/blog\/linear-regression-example\/","title":{"rendered":"Linear Regression Example"},"content":{"rendered":"

 <\/p>\n

Task:<\/b><\/p>\n

Based on the findings of two random variables, find the linear regression of X on Y and the selective correlation coefficient.<\/span><\/p>\n

\"\"<\/a><\/p>\n

<\/p>\n

Solution:<\/b><\/p>\n

Let’s build a correlation field:<\/span><\/p>\n

We can assume a linear relationship between these values.<\/span><\/p>\n

\"\"<\/a><\/p>\n

Let\u2019s construct a table of calculated data for the evaluation of the linear regression:<\/span>\"\"<\/a><\/p>\n

Let’s find the parameters of the linear regression:<\/span><\/p>\n

\"\"<\/a><\/p>\n

Thus, the regression equation is:<\/span><\/p>\n

\"\"<\/a><\/p>\n

We can make a conclusion that by increasing x value on 1, y will increase on 1,25.<\/span><\/p>\n

Let\u2019s find selective correlation coefficient:<\/span><\/p>\n

\"\"<\/a><\/p>\n

The correlation coefficient is close to 1, so the relationship between the factors is strong.<\/span><\/p>\n

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 <\/p>\n","protected":false},"excerpt":{"rendered":"

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