Statistical Analysis

Descriptive Statistics

Descriptive 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:

• Skew
• Measures of central tendency (mean, median or mode)
• Measures of Spread (range, standard deviation or  quartiles)
• Correlation coefficient

Inferential Statistics

Inferential statistics are mathematical calculations performed to determine if the results from your sample of data are likely due to chance or are a true representation of the population. Inferential statistics are used to determine the probability of chance alone leading to your sampled results.  More about inferential statistics is available here.  

Common descriptive statistics used in IB Biology are: 

• T-Test 
• ANOVA 
• Kruskal-Wallis 
• Chi-Square Goodness of Fit 
• Pearson's Correlation (bottom of the page) 
• Spearman's Rank Correlation
• ​Chi-Square Test of Independence

---

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.​