Statistics/Proofreading

Statistics/Proofreading

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Statistical Analysis

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01. Basic statistics Descriptive statistics
Frequency analysis
Cronbach alpha coefficient
Normality test
Levene's test
Independent two-sample t test
Chi-squared test
Analysis of variance; ANOVA
02. Intermediate statistics Multivariate analysis of variance; MANOVA
Repeated measures ANOVA
Factor analysis
Correlation analysis
Canonical correlation analysis
Simple regression analysis
Multivariate regression analysis
Discriminant analysis
03. Advanced statistics Logistic regression analysis
Hierarchical regression analysis
Generalized estimating equation; GEE
Cox proportional hazard model
Poisson Regression analysis
Structural Equation Modeling; SEM
Generalized Linear Modeling; GLM
Time series analysis

Statistics software

Statistical pakage

Software developed to facilitate data processing and statistical analysis in a wide range of fields

Retention programs SPSS Statistics 25.0 SAS 9.4 R 3.5.3 Python 3.7 AMOS 24 MINITAB 18
STATA 15 Jupyter notebook
SPSS Used for data entry, management and statistical analysis in a wide range of fields including social sciences
All analysis procedures are organized in a menu method, and data input and management are easy (Korean language support)
SAS As an integrated package, it has excellent data processing capabilities.
A system that helps decision-making through processing vast amounts of data and analyzing various data.
Minitab Statistical software developed to handle the analysis of various data in the menu method, making it easy to create graphs
AMOS Statistical software for structural equation model analysis
Python A high-level programming language, platform-independent, interpreted, object-oriented, and dynamic typing
interactive language used by many products, companies, and research institutes.

Data analysis according to the time of investigation

cross-sectional study

A research method that compares research subjects at a certain point in time

 

Longitudinal study

A research method that identifies the change status of various variables over time by sampling a research target group at a certain point in time and repeatedly observing them over a long period of time Trend study, cohort study, panel study (panel study)

Category Cross-sectional study Longitudinal study
Advantages ・Easy data collection
・Economical		 ・It is easy to understand the change factors of variables
・Causal relationship can be identified.
Disadvantages ・Analysis that reflects the passage of time is difficult
・Difficulty in understanding causality		 ・Time consuming and expensive.
・It is possible that the reaction behavior of the same study subject may vary depending on the time point.
・If the sample of the study subject that has been continuously managed for a long time is lost, it causes difficulties in analysis.
Main analysis method ・Multivariate regression analysis
・Discriminant analysis
・Stepwise regression analysis
・Logistic regression analysis
・Hierarchical regression analysis
・Structural equation modeling; SEM		 ・Repeated measures ANOVA
・Generalized estimating equation; GEE
・Kaplan-Meier survival analysis, Cox proportional hazard model
・Generalized linear modeling; GLM
・Time series analysis