Which is better bioinformatics or biostatistics
What is the difference between statistics and computer science?
We always say that statistics are only about data. But we also know that computer science also receives knowledge from data analysis. For example, bioinformatics people can do without biostatistics entirely. I would like to know what is the main difference between statistics and computer science.
Excellent question !!
I have heard several times that bioinformaticians can do without biostatistics or even without statistics. That is perfectly true until it becomes false. In my opinion, the general lack of statistical knowledge is having disastrous effects in this area, as Keith Baggerly has shown. I was also able to observe that a lack of basic knowledge in statistics (and linear algebra) is the cause of the stagnation of bioinformaticians in the long run: without deep knowledge of the theory, they tend to reinvent the wheel and on Ad hoc- To fall back on solutions that solve nothing but their own problem.
To answer your question, I agree that statistics cannot generally do without computers these days. However, one of the main aspects of statistics is that Inference that has nothing to do with computers. Statistical inference is actually what makes statistics a science because it tells you whether or not your conclusions hold up in other contexts.
In short, you can the hell analyze your data. You will still need statistics to get the validity the predictions or decisions you will make based on your analysis.
In my opinion, while there is considerable overlap between the fields, there are also important differences. In general, a statistics student (in the advanced degrees) takes more theory classes (math and math) than the computer science student, but the computer science student learns more about the computer side (especially the database part).
Developing a new statistical test would be left to the statistician rather than the computer scientist, but designing an interface for a user to enter data and create tables and plots would be left to the computer scientist rather than the statistician.
For the statistician, the computer is a tool for statistics. For the computer scientist, statistics are a tool to collect and disseminate information (about computers in general).
Edit down here -----
For example, here is an example. I've worked on projects with computer scientists (I'm the statistician) where a doctor wants a system where information about patients is used to predict the risk of a disease (e.g. developing a blood clot), and a Would like to receive form of alert to inform them of the risk. My role in the project (the statistical role) is to develop a model that predicts risk taking into account the predictor variables (a logistic regression model is one such model). The computer science role in the project is to develop the tools to capture the predictor variables, apply my model to them, and then send the results to the doctor. The data can be collected from an electronic medical record or through a data entry screen that a nurse can fill in, or through others.
Now, I (and many other statisticians) know enough about programming that I could query a database to get the predictors and create some kind of alarm, but I like to leave that to the computer scientists (and they're better at it anyway). There are computer scientists who know enough statistics to fit the logistic regression model. So a simple version of this project could just be done by a statistician or just a computer scientist, but it is best if the two of them work together. If you look at this project and think that the modeling part is the fun part, and the data collection, warning, and other interfaces are just tools to move the information to and from the model, you are more of a statistician. When you see UI designing, data retrieval tweaking, testing different types of warnings, and so on.
statistics concludes from the data; The IT is working with data. Of course they overlap, but the question of which is the larger has no answer.
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