parent nodes: Support

# Introduction to Statistics lang: en_US

## Why use statistics

Statistics is a robust way to analyses data in order to make decisions.
• Present the data graphical
• If data is significant different
• If data is has the same shape distribution

## Graphs

### Control/time chart • Monitor to production process
• Behavior over time

### Correlation Graph Correlation Graph To find correlations There is a correlation as the value on the X-axle is having influence on the Y-axle (see A-D)

### Histogram  Histogram shape of distribution and position of your data

## Data shape and variation

### Big Variation  ## Why is a lot of data normally distributed

Variation of is often caused by multiple factors
 Example resistance of a light-bulb • Length of the wire • Material of the wire • Diameter of the wire • Internal connection of the wire • External connection of the bulb

Adding up all these distributions will create normally distributed data due to the Central limit theorem.

### Central limit theorem The summarizing independent distributions results in a approximately normally distributed data. Even if the independent distribution are not normally distributed.

## Normal assumption

Due the Central limit theorem most data is normally distributed and a lot of statistics assume normality. ## What can we do with this?

 • Check if data is within tolerance • Determine if there is a significant difference in Mean or Variation  • If there is a correlation between to data sets 