# Logarithmic transformations

## Logarithmic transformations can normalize skewed or kurtotic data for purposes of analysis

Logarithmic transformations are used to "

The means and standard deviations of these transformed variables cannot be interpreted in the traditional sense. Only the

**normalize**" skewed or kurtotic distributions of continuous variables so that parametric statistics can be conducted. Essentially, all that researchers are doing with a logarithmic transformation is taking the natural log (ln) of each observation in the distribution. Non-normal distributions often have "outliers" or observations that are more than 3.29 standard deviations away from the mean. By transforming the distribution with a logarithmic transformations, these observations are "forced" closer to the mean and will generate a more normal distribution.The means and standard deviations of these transformed variables cannot be interpreted in the traditional sense. Only the

*p*-value yielded from the analysis can be interpreted.**Medians**and**interquartile ranges**for the respective distributions should be reported for descriptive purposes.### The steps for conducting logarithmic transformations in SPSS

1. Click

2. Click

3. In the

4. Click on the continuous outcome variable to highlight it.

5. Click on the

6. Type "

7. Click

8. In the

**.**__T__ransform2. Click

**.**__C__ompute Variable3. In the

**box, give the outcome a new name that reflects it has been transformed.**__T__arget Variable:4. Click on the continuous outcome variable to highlight it.

5. Click on the

**arrow**button to bring the variable over into**Num**box.__e__ric Expression:6. Type "

**ln"**and put**parentheses**around the variable. Example:**ln(outcome)**7. Click

**OK**.8. In the

**Data View**tab of SPSS, there is a new transformed outcome variable.## Hire A Statistician - Statistical Consulting for Students

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