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# Inferential statistics

## lab

### Why?

To test hypotheses based on a quantitative dataset.

### How?

First, perform descriptive statistics. Next, formulate a hypothesis that can be expressed in variables of your dataset. Test your hypotheses using an appropriate statistical test. Every test makes certain assumptions about the character of your data; make sure your data complies with these assumptions.

### Ingredients

- A well-defined dataset and hypotheses
- Statistical software such as SPSS, R or Excel
- Advanced knowleddge about statistics and probablity theory
- A keen eye for the differnce between signal and noise.

### In practice

With the advent of big data, inferential statistics are increasingly important. However, inferential statistics are delicate and companies often use spacialists to analyze them. Novices commonly make errors like ‘capitalizing on chance’. This happens when an analyst tests so many hypotheses that some turn out ‘positive’ by accident.

### Phase(s) of use

In the following project phase(s) inferential statistics can be used:

- Realisation