Statistical Analysis
Statistics is a field of mathematics that is used to quantitatively describe the variability inherent in data, the probability of certain outcomes, and the uncertainty associated with those outcomes. Statistical methods are used extensively throughout the scientific process, from the design of research questions through data analysis and to the final interpretation of data.
Many statistical techniques have been developed for data analysis, but they generally fall into two groups: descriptive and inferential.
Many statistical techniques have been developed for data analysis, but they generally fall into two groups: descriptive and inferential.
Descriptive StatisticsDescriptive statistics help to summarize data. Descriptive statistics do not allow you to make conclusions beyond the data you have collected or reach conclusions regarding any hypotheses you might have made. They are simply a way to describe your data. Descriptive statistics are very important because if you simply presented your raw data it would be hard to visualize what the data was showing, especially if there was a lot of it. Common descriptive statistics used in IB Biology are:
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Inferential StatisticsInferential statistics are mathematical calculations performed to determine the probability of observing a certain result. Inferential statistics are used to assess how likely the results from a smaller sample are a true representation of the larger population. More about inferential statistics is available here. Common descriptive statistics used in IB Biology are:
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Students in IB biology are expected to have acquired competence in the areas of mathematics set out below in order to develop the knowledge, understanding and skills in the subject content. All IB biology students should be able to:
- Perform the basic arithmetic functions: addition, subtraction, multiplication and division.
- Recognize basic geometric shapes.
- Carry out simple calculations within a biological context involving means, decimals, fractions, percentages, ratios, approximations, reciprocals and scaling.
- Use standard and scientific notation.
- Recognize direct and inverse proportion.
- Represent and interpret frequency data in the form of bar charts, column graphs, histograms and pie charts.
- Determine the mean, mode and median of a set of data.
- Plot and interpret graphs (with suitable scales and axes) involving two variables which show linear or non-linear relationships.
- Plot and interpret scatter graphs to identify a correlation between two variables, and appreciate that the existence of a correlation does not establish a causal relationship.
- Demonstrate sufficient knowledge of probability to understand how Mendelian ratios arise and to calculate such ratios using a Punnett grid.
- Recognize and use the relationships between length, surface area and volume.