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It is a serious error.

The Pearson coefficient cannot be larger than 1 so a value of 64 is clearly a very big error.

Q: What is the Pearson correlation coefficient of 64?

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From Laerd Statistics:The Pearson product-moment 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 product-moment 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 (how well the data points fit this new model/line of best fit).

Yes it can be a correlation coefficient.

No, it cannot be a correlation coefficient.

Evidence that there is no correlation.

A coefficient of zero means there is no correlation between two variables. A coefficient of -1 indicates strong negative correlation, while +1 suggests strong positive correlation.

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From Laerd Statistics:The Pearson product-moment 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 product-moment 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 (how well the data points fit this new model/line of best fit).

Yes.The Pearson correlation coefficient ranges from -1 to 1 inclusive.The sign of the coefficient tells you the kind of correlation:positive: as one variable increases the other also increases (like y = x)negative: as one variable increases the other decreases (like y = -x)0 means no correlation |r| = 1 means perfect correlation

Pearson's Product Moment Correlation Coefficient indicates how strong the relationship between variables is. A PMCC of zero or very close would mean a very weak correlation. A PMCC of around 1 means a strong correlation.

Either an Interval or an Ordinal Scale

The nominal variant will be for males (1) and for females (3) to identify the relation in the study.

The PEARSON(array1, array2) function returns the Pearson product-moment correlation coefficient between two arrays of data. See related links for specific instructions.

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If two variables are highly correlated, the Pearson correlation will be close to -1.0 or +1.0. A correlation of zero shows no relationship.

Yes it can be a correlation coefficient.

No, it cannot be a correlation coefficient.

The PEARSON(array1, array2) function returns the Pearson product-moment correlation coefficient between two arrays of data. See related links for specific instructions.

No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).