What Is Data Transformation?
Data transfer is the process of changing data from one representation to another.
- The comprehensive upgrade of the software will definitely bring about the comprehensive upgrade of the database. Each software has a different database structure and data storage form behind it, which requires data conversion.
- Mainly due to the increasing amount of data, the original data structure was unreasonable and could not meet the requirements of various parties. The replacement of the database and the change of the data structure require the conversion of the data itself.
- Data conversion must be paid attention to, and can not be converted at all costs, because sometimes the conversion will seriously distort the meaning of the data itself. Example: Box-Cox conversion must be used with caution. This method that can convert almost all data will change the original form of the data. For example, the average of the first group is greater than the second group, but after conversion, the two groups of data can be converted. No difference. Even get the opposite result. Therefore, you cannot use overly complex conversion methods. However, in many cases, conversion is a good method if it is done properly.
Data Conversion Logarithmic Conversion
- Use the natural logarithmic value of the original data as the analysis data. If there are zeros in the original data, you can add a decimal value to the base.
- Application:
- Some positive skew data.
- Equivalence data.
- Data with little difference between the values of the groups and the mean ratio.
Data conversion square root conversion
- Application:
- Obey the data of [1] Poisson distribution.
- Slightly skewed data.
- The sample's variance and mean are positively correlated.
- All the data of the variables are percentages, and the values are from 0% to 20% or 80% to 100%.
Data conversion square root arc sine conversion
- Applicability: All cases in the variable are percentages and data with a wide range of values.
Data conversion square conversion
- Application:
- The variance and the square of the mean are inversely proportional.
- The data is left-biased.
Data conversion inverse transform
- Applicable situation: In contrast to the square conversion, the variance and the square of the mean need to be proportional, but the inverse conversion requires that there is no data near or less than zero in the data.
- Data conversion operation in spss:
- "Analysis" ~ "Descriptive Statistics" ~ "PP Graph" ~ Select the variables you need to analyze ~ "Conversion" column ~ there will be a corresponding conversion.
- Result: If almost all the scattered points of the [2] PP graph of the transformed variables are concentrated on a diagonal line, that is, the PP line, it means that the transformed data follows a normal distribution, that is, the transformation is successful.