easier R than SPSS with Rcmdr : Contents
ch.38 Variable standardization
You can standardize numeric variables.
Select 1 or more variables.
The name of the variable is automatically generated, with an average of 0 and a standard deviation of 1 for these numbers. In other words, after calculating the mean and standard deviation of the original value, the average is subtracted from each value and then divided by the standard deviation to standardize it.
If the units of length are different, such as meters and feet, standardizing will eliminate the difference. Standardization is also used a lot when comparing the relative effects of variables with completely different units of measurement, such as height and weight. However, I am very careful when interpreting it. In other words, if you are tall, ‘when you increase by 1’ means that you have increased by not 1 meter, not 1 centimeter, not 1 foot, and increased by 1 standard deviation, so you won’t know how much it actually is unless you look at it.
easier R than SPSS with Rcmdr : Contents
=================================================
- R statisics portal https://tinyurl.com/stat-portal
- R data visualization book 1 https://tinyurl.com/R-plot-I (chart)
- R data visualization book 2
https://tinyurl.com/R-plot-II-3-4 many variables / map
https://tinyurl.com/R-plot-II-5-6 time related / statistics related
https://tinyurl.com/R-plot-II-7-8 others / reactive chart
- R data visualization book 3 https://tinyurl.com/R-data-Vis3
- R data visualization book 4 R 데이터 시각화 4권
- Meata Analysis book 1 https://tinyurl.com/MetaA-portal
- Meata Analysis book 2 https://tinyurl.com/MetaA-portal(2)
- Preciction Model and Machine Learning https://tinyurl.com/Machine-Learning-EZ
- Sample Size Calculations https://tinyurl.com/MY-sample-size
- Sample data https://tinyurl.com/data4edu
댓글 없음:
댓글 쓰기