# How does R compare to SPSS

## Compare correlations statistically

**computer**

Just like other statistics, correlations can be compared with one another. The calculation depends on the type of correlations and the sample. The three possible cases are discussed here and can be calculated directly.

### Three different comparisons

The division primarily distinguishes whether the correlations both come from the same sample (i.e. are dependent) or from two different samples (i.e. are independent). In total, three different types of correlation comparisons can be made:

- compare two correlations from two different samples (independent)
- compare two correlations from a sample that have a third variable in common
- compare two correlations from a sample that
*no*Have third variables in common

### Independent groups

Usually we will have two correlations from two independent groups that we want to statistically compare. This can be the case, for example, if we want to compare the correlations from two different studies with one another or if the sample is independent of one another.

For example, we might want to compare the correlation coefficients from two studies on intelligence and life satisfaction. Both studies would indicate correlation coefficients for intelligence and life satisfaction, which we could statistically compare with specifying the sample size.

### Dependent groups, with a third variable

Alternatively, we can also compare the correlation within a sample (dependent). One possibility here is that the two correlations are overlapping and therefore have one variable in common. For example, we might want to compare the correlations of intelligence and life satisfaction with the correlation of intelligence and income. Since the significance is based on the intercorrelation between life satisfaction and income, this correlation must also be specified as a parameter.

### Dependent groups, no third variable

Finally we want to compare two correlations of dependent groups that have no third variable in common. For example, we might want to know whether the correlation between intelligence and income and between life satisfaction and expectations of self-efficacy are statically different. Since the significance depends on all intercorrelations involved, they must be specified as parameters.

### computer

**Calculate Significances**

#### Quote this calculator

### bibliography

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*American Educational Research Journal*,*7*(2), 189. doi: 10.2307 / 1162159 - Hittner, J.B., & May, K. (1998). DEPCORR: A SAS Program for Comparing Dependent Correlations.
*Applied Psychological Measurement*,*22*(1), 93-94. doi: 10.1177 / 01466216980221010 - Hotelling, H. (1940). The Selection of Variates for Use in Prediction with Some Comments on the General Problem of Nuisance Parameters.
*The Annals of Mathematical Statistics*,*11*(3), 271-283. doi: 10.1214 / aoms / 1177731867 - May, K., & Hittner, J.B. (1997a). Tests for Comparing Dependent Correlations Revisited: A Monte Carlo Study.
*The Journal of Experimental Education*,*65*(3), 257-269. doi: 10.1080 / 00220973.1997.9943458 - May, K., & Hittner, J.B. (1997b). A note on statistics for comparing dependent correlations.
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