easier R than SPSS
with Rcmdr
Written by Jeehyoung Kim
foreword
This book covers statistical tests for beginners.
Some time ago I was talking with a professor of statistics, who told me that she wanted to have a program that was suitable for teaching students. SPSS is an easy GUI method to teach to the general public, but it’s expensive. Because R is script-based, it is difficult to teach to the general public.
Rcmdr provides easier menu configuration and more intuitive results and graphs than SPSS. It is also highly expandable and will be a bridge that leads to a wider world of R.
The first target readers I considered in writing this book is the students. The second readers are the professors who teach the students. Most of professors will be familiar with R, SAS, or SPSS. But what professors are familiar with and what professors tell their students about it is another completely different part of the challenge. I have that difficulty, too. If you’re looking for a program with easy-to-teach menus, a program that’s never lacking in functionality, first take a quick look at this book. Then you’ll find that this is a tool that’s easier to learn and use than SPSS.
Aug 2022
Jeehyoung Kim
Contents
Part 1 Basic Statistics
ch.3 Nomality test and Variances test
Part 2 (ch. 14-16) Survival Analysis
ch.14 KM curve and log-rank test
Part 3 (ch. 17-19) Statistics on Diagnosis
ch.18 Sensitivity and Specificity
ch.19 Kappa statistics for agreement
Part 4 (ch. 20-22) Analysis of paired data
ch.20 Paired t-test and Wilcoxon signed rank test
ch.21 Repeated-Measures ANOVA and Friedman test
ch.22 McNemar test Cochran Q test
ch.23 Propensity Score Matching and Analysis
Part 5 (ch. 24-27) Dimensional Analysis
ch.24 Principal Component Analysis (PCA)
ch.27 Factor analysis and cluster analysis
Part 6 (ch. 28-34) Samples Size Calculation
ch.28 proportion of two groups
ch.30 paired mean of two groups
ch.34 Meaning of sample size (power) calculation
Part 7 (ch. 35-41) Uploading and Editing Data
ch.37 Calculating and inserting new variables
ch.38 Variable standardization
ch.39 Continuous variable as interval variable
ch.40 number as a nominal variable
ch.42 Original menu and New menu
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- 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