Pearson Product Moment

Pearson Product Moment. What is the Pearson productMoment Correlation? In statistics it’s a measuring tool to determine whether there is a linear relationship between two variables – or not It quantifies the strength and the direction of the relationship which can be identified by the correlation coefficient.

The correlation coefficient is also known as the Pearson ProductMoment Correlation Coefficient The sample value is called r and the population value is called r (rho) The correlation coefficient can take values between 1 through 0 to +1 The sign (+ or ) of the correlation affects its interpretation.

Pearson Correlation Formula Pearson correlation

The Pearson productmoment correlation coefficient (or Pearson correlation coefficient for short) is a measure of the strength of a linear association between two variables and is denoted by r Basically a Pearson productmoment correlation attempts to draw a line of best fit through the data of two variables and the Pearson correlation coefficient r indicates how far away all these data points are to this line of best fit (ie how well the data points fit this new model/line of best.

Pearson ProductMoment Correlation: A Relationship

It is also known as the Pearson productmoment correlation coefficient The value of the Pearson correlation coefficient product is between 1 to +1 When the correlation coefficient comes down to zero then the data is said to be not related.

Pearson Product Moment Correlation Coefficient

FormulaThings to Remember About The Pearson FunctionAdditional Resources=PEARSON(array1 array2) The PEARSON function uses the following arguments 1 Array1(required argument) – This is the number set of independent values 2 Array2 (It is a required argument) – This is the set of dependent values The function ignores text values and logical values that are supplied as part of an array The Pearson productmoment correlation coefficient for two sets of values x and y is given by the formula Where x and yare the sample means of the two arrays of values If the value of r is close to +1 it indicates a strong positive correlation and if ris close to 1 it denotes a strong negative correlation #N/A! error – Occurs if the given array arguments are of different lengths#DIV/0! error – Occurs when either of the given array arguments is empty or when the standard deviation of their values is equal to zeroThe PEARSON function performs the same calculation as the CORREL function However in MS Excel 2003 and earlier versions PEARSON may exhibit some rounding errorsIf an array or reference argument contains text logical values or empty cells the values are ignored However cells with the value zero are included by this function Thanks for reading CFI’s guide to important Excel functions! By taking the time to learn and master these functions you’ll significantly speed up your financial modeling To learn more check out these additional CFI resources 1 Excel Functions for FinanceExcel for FinanceThis Excel for Finance guide will teach the top 10 formulas and functions you must know to be a great financial analyst in Excel 2 Advanced Excel Formulas Course 3 Advanced Excel Formulas You Must KnowAdvanced Excel Formulas Must KnowThese advanced Excel formulas are critical to know and will take your financial analysis skills to the next level Download our free Excel ebook! 4 Financial Analyst Certification ProgramBecome a Certified Financial Modeling & Valuation Analyst (FMVA)®CFI&#39s Financial Modeling and Valuation Analyst (FMVA)® certification will help you gain the confidence you need in your finance career Enroll today!.