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Statistics Tutorial
This statistics tutorial is a guide to help you understand key concepts of statistics and how these concepts relate to the scientific method and research.
Scientists frequently use statistics to analyze [1] their results. Why do researchers use statistics? [2] Statistics can help understand a phenomenon by confirming or rejecting a hypothesis. It is vital to how we acquire knowledge to most scientific theories.
You don't need to be a scientist though; anyone wanting to learn about how researchers can get help from statistics may want to read this statistics tutorial for the scientific method.
What is Statistics? [3]
Research Data
This section of the statistics tutorial is about understanding how data is acquired and used.
The results of a science investigation often contain much more data or information than the researcher needs. This data-material, or information, is called raw data.
To be able to analyze the data sensibly, the raw data is processed [4] into "output data [5]".
There are many methods to process the data, but basically the scientist organizes and summarizes the raw data into a more sensible chunk of data. Any type of organized information may be called a "data set [6]".
Then, researchers may apply different statistical methods to analyze and understand the data better (and more accurately). Depending on the research, the scientist may also want to use statistics descriptively [7] or for exploratory research.
What is great about raw data is that you can go back and check things if you suspect something different is going on than you originally thought. This happens after you have analyzed the meaning of the results.
The raw data can give you ideas for new hypotheses, since you get a better view of what is going on. You can also control the variables which might influence the conclusion [8] (e.g. third variables [9]). In statistics, a parameter [10] is any numerical quantity
Statistics Tutorial
This statistics tutorial is a guide to help you understand key concepts of statistics and how these concepts relate to the scientific method and research.
Scientists frequently use statistics to analyze [1] their results. Why do researchers use statistics? [2] Statistics can help understand a phenomenon by confirming or rejecting a hypothesis. It is vital to how we acquire knowledge to most scientific theories.
You don't need to be a scientist though; anyone wanting to learn about how researchers can get help from statistics may want to read this statistics tutorial for the scientific method.
What is Statistics? [3]
Research Data
This section of the statistics tutorial is about understanding how data is acquired and used.
The results of a science investigation often contain much more data or information than the researcher needs. This data-material, or information, is called raw data.
To be able to analyze the data sensibly, the raw data is processed [4] into "output data [5]".
There are many methods to process the data, but basically the scientist organizes and summarizes the raw data into a more sensible chunk of data. Any type of organized information may be called a "data set [6]".
Then, researchers may apply different statistical methods to analyze and understand the data better (and more accurately). Depending on the research, the scientist may also want to use statistics descriptively [7] or for exploratory research.
What is great about raw data is that you can go back and check things if you suspect something different is going on than you originally thought. This happens after you have analyzed the meaning of the results.
The raw data can give you ideas for new hypotheses, since you get a better view of what is going on. You can also control the variables which might influence the conclusion [8] (e.g. third variables [9]). In statistics, a parameter [10] is any numerical quantity