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Statistics Introduction

Statistics gives us methods of gaining knowledge from data.

What is Statistics Used for?

Statistics is used in all kinds of science and business applications.

Statistics gives us more accurate knowledge which helps us make better decisions.

Statistics can focus on making predictions about what will happen in the future. It can also focus on explaining how different things are connected.

Note: Good statistical explanations are also useful for predictions.

Typical Steps of Statistical Methods

The typical steps are:
  • Gathering data
  • Describing and visualizing data
  • Making conclusions

It is important to keep all three steps in mind for any questions we want more knowledge about.

Knowing which types of data are available can tell you what kinds of questions you can answer with statistical methods.

Knowing which questions you want to answer can help guide what sort of data you need. A lot of data might be available, and knowing what to focus on is important.

How is Statistics Used?

Statistics can be used to explain things in a precise way. You can use it to understand and make conclusions about the group that you want to know more about. This group is called the population.

A population could be many different kinds of groups. It could be:

  • All of the people in a country
  • All the businesses in an industry
  • All the customers of a business
  • All people that play football who are older than 45

and so on - it just depends on what you want to know about.

Gathering data about the population will give you a sample. This is a part of the whole population. Statistical methods are then used on that sample.

The results of the statistical methods from the sample is used to make conclusions about the population.

Note: The word 'statistic' can also refer to specific bits of knowledge; like the average value of something.

Important Concepts in Statistics

  • Predictions and Explanations
  • Populations and Samples
  • Parameters and Sample Statistics
  • Sampling Methods
  • Data Types
  • Measurement Level
  • Descriptive Statistics
  • Random Variables
  • Univariate and Multivariate Statistics
  • Probability Calculation
  • Probability Distributions
  • Statistical Inference
  • Parameter Estimation
  • Hypothesis Testing
  • Correlation
  • Regression Analysis
  • Causal Inference

We will cover these topics step by step in this tutorial.