# Features of outputs in the Area 3

Statistical results includes statistical tables and plots.

## 1. Statistical tables

Most tables in MEPHAS are shown by DT package.

Tables are shown for

**Data Preview**and display the**Results**The tables are easy to save and search numbers

## 2. Statistical plots

## 2.1. Three types of plots

Plots in MEPHAS are shown by ggplot2 package and plotly package. **2D ggolot, 2D plotly, and 3D plotly** are used in MEPHAS. These plots are easy to save.

- Save ggolot2 plots: right click can save the plot as image

- Save 2D plotly plots: click the camera icon.

- Save 3D plotly plots: click the camera icon. 3D plots need some time to load.

## 3. The overview of statistical plots

### 3.1. 2D ggplot

- Distribution plot

### 3.2. 2D plotly

#### 3.2.1. To plot distribution

Histogram

Density plot

QQ plot

#### 3.2.2. To plot descriptive statistics

Box plot

Mean and SD plot

#### 3.2.2. To plot proportion

Pie plot

Bar plot

#### 3.2.3. Plots in ANOVA

- Mean plot in line to show the marginal mean plot

#### 3.2.4. Plots in Linear regression

Scatter plot between 2 continuous variables

Residuals plot

#### 3.2.5. Plots in logistic regression

Scatter plot between binary variable and continuous variable

ROC plot

#### 3.2.6. Plots in survival analysis

Survival / Hazard plots

Martingale residuals, deviance residuals, and Cox-snell residuals plot

Integrated Brier score plot

Time-dependent AUC plot

#### 3.2.6. Plots in PCA and EFA

Parallel analysis plot to decide the number of components

Correlation matrix plot

#### 3.2.6. Plots in PCA, EFA, PCR, PLSR, and SPLSR

Component plot

Loading plot

Biplot for component and loading

### 3.3. 3D plotly

3D Scatter plot in linear regression

3D biplot in dimensional analysis