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There are lots of applications of statistics in bioinformatics - it is one of the central areas of studies when learning bioinformatics. For example, students have to learn about Bayesian and Frequentist statistics as well as Hidden Markov Models (HMMs). Statistics can answer questions such as, "what is the likelihood that these two DNA sequence alignments are due to them being homologous?" or "given that this sequence looks like this, what is the probability that it is a gene?"

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There are lots of applications of statistics in bioinformatics - it is one of the central areas of studies when learning bioinformatics. For example, students have to learn about Bayesian and Frequentist statistics as well as Hidden Markov Models (HMMs). Statistics can answer questions such as, "what is the likelihood that these two DNA sequence alignments are due to them being homologous?" or "given that this sequence looks like this, what is the probability that it is a gene?"

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The two main branches of statistics is Descriptive statistics and inferential statistics.

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There are two types of statistics. One is called descriptive statistics and the other is inferential statistics. Descriptive statistics is when you use numbers. Inferential statistics is when you draw conclusions or make predictions.

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Psychological statistics is the application of statistics to psychology.

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The statistics (pl.) indicate that statistics (sing.) is a pseudo-science.

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