Bioinformatik

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Flashcards on Bioinformatik , created by Alicia L on 13/09/2024.
Alicia L
Flashcards by Alicia L, updated about 2 months ago
Alicia L
Created by Alicia L about 2 months ago
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Question Answer
What is (Bio)informatics? 1. Application of statistical methods to scientific research in biology and medicine 2. Development of new tools 3. answer scientific questions
What are general steps to solve a scientific question? 1. identify a problem 2. collect data 3. analyse the data 4. conclusion
What two types of statistical methods are there? 1. Descriptive statistics 2. inferential (schließende) statistics
What is descriptive statistics? - how can we summarize and reduce the data? f.ex. with a Histogramm or with descriptive tools such as mean, sd, median...
What is inferential statistics? - what can we infere, what can we conclude from the data? - testing a hypothesis, making predictions about a population f.ex.: t-test
How do we measure the median, mean and mode? Median: (middle value when data is sorted) mean: (Sum of the values devided by the numbers of values ) mode: (most common value)
How to we measure the variance and the standard deviation SD= distance from the mean Variance= squared distance from the mean
What are the two types of data? Numerical and categorical
What are numerical data? Quantitative (can be measured numerically) Can be Continous (height, infinitive number of decimals) Can be discrete (full numbers or maximum restricted number of values, children can´t be countd in half)
What is categorical data Qualitative data Can be devided into groups or categories f.ex. hair color, education etc
How cann you organize data? stacked data: Each row is for one individual • Information for multiple variables is possible • Should be the primary way to store raw data Unstacked data • Divides data in groups • Can only take two variables at the time • This format is useful for some statistical tests two way tables categorical data can implement two variables (group 1,2 for eye colour blue and brown)
What is complete and incomplete data? incomplete data: cruicial data is missing!
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