# Statistical analysis

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Statistical analysis

## 1. Descriptive statistics

### 1.1. Quantitative data

1.1.1. types

1.1.1.1. continuous

1.1.1.2. discrete

1.1.2. measures

1.1.2.1. central tendency

1.1.2.1.1. skewed data

1.1.2.1.2. normal distribution

1.1.2.2.1. for normal distribution

1.1.2.2.2. for skewed data

### 1.2. Qualitative data

1.2.1. Types

1.2.1.1. categorical (nominal)

1.2.1.1.1. dichotomous

1.2.1.2. ordinal

1.2.2. Measures

1.2.2.1. percentages

## 2. Comparative statistics

### 2.1. Quantitative data and Quantitative data

2.1.1. correlation analysis

2.1.1.1. linear regression/multiple linear regression for causation

### 2.2. Qualitative data and Qualitative data

2.2.1. sample more than 40

2.2.1.1. Chi-square test

2.2.1.1.1. Logistic regression for causation

2.2.1.1.2. Odds ratio 2x2 table

2.2.2. sample less than 40

2.2.2.1. Fissure exact test

2.2.3. Odds ratio and relative risk can be used if comparing dichotomous data with dichotomous data (2x2 table)

### 2.3. Qualitative data and Quantitative data

2.3.1. if quantitative data are normally distributed, use parametric statistics

2.3.1.1. qualitative data 2 groups only (male and female)

2.3.1.1.1. Student T test

2.3.1.2. more than 2 groups

2.3.1.2.1. ANOVA test

2.3.2. if quantitative is skewed, use non parametric statistics

2.3.2.1. qualitative data 2 groups only (male and female)

2.3.2.1.1. Mann-Whitney U test

2.3.2.2. more than 2 groups

2.3.2.2.1. Krskle-Wallis test