Step-by-step method for Excel to use the Correl function to return correlation coefficients and determine attribute relationships-Office Software-php.cn

Step-by-step method for Excel to use the Correl function to return correlation coefficients and determine attribute relationships

王林

Apr 17, 2024 pm 07:25 PM

Calculation of correlation coefficient How to determine the strength of the relationship between two attributes is a key issue in data analysis. PHP editor Baicao will show you how to use the CORREL function in Excel to calculate the correlation coefficient to quantify the linear relationship between attributes. This article will introduce the steps of using this function in detail to help you effectively grasp the relationship between attributes.

Start Excel, open the table, and enter the formula in the cell after the correlation coefficient: =CORREL($B$2:$B$13,C2:C13)

Step-by-step method for Excel to use the Correl function to return correlation coefficients and determine attribute relationships

Return Car, the result is 0.75114738. I will explain the meaning of the result to you later.

Step-by-step method for Excel to use the Correl function to return correlation coefficients and determine attribute relationships

Fill cells to the right and complete subsequent data calculations.

Step-by-step method for Excel to use the Correl function to return correlation coefficients and determine attribute relationships

Formula description

Correl(array 1, array 2): Returns the correlation coefficient between the two sets of arrays. The correlation coefficient can be used to determine the correlation between the two attributes. relation.

Returns the correlation coefficient between the average temperature and air conditioning. Through this correlation coefficient, the relationship between temperature and air conditioning is analyzed.

Explanation

The closer the correlation coefficient is to 0, the less relevant the two are. For example, the calculated correlation coefficient between TV and temperature is closest to 0, indicating that TV is generally not affected by temperature. The result of air conditioning is closer to 1, indicating that air conditioning has a positive correlation with temperature. The higher the temperature, the more air conditioners are sold; vice versa. As for electric blankets, there is an inverse correlation. The higher the temperature, the less they are sold, and the lower the temperature, the more they are sold.

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