The ERS fellowship portfolio: fostering excellence and diversity

Measuring Biodiversity in Areas with Different Disturbance Regimes
ExpandNOTE: In this experiment, you will compare the biodiversity in a less disturbed area against a more highly disturbed area. HYPOTHESES: The experimental hypothesis could be that a less disturbed area will contain a greater diversity of species than a highly disturbed area. The null hypothesis could be that there will be no difference in diversity between less disturbed and highly disturbed areas.
To begin, divide into...

Setting up for the Lab and Choosing Field Sites
ExpandBefore the experiment, first ensure that the student computers have Microsoft Excel or Google Sheets installed.
If using Excel, make sure the data analysis tool pack is loaded.
Next, you will need to identify the two fields where the students will take measurements. Both fields should ideally have lengths in any direction of at least 30 meters. One field should be a shrubby or weedy field that has not been mowed recently. The second field...

Populations do not live in isolation; thus, every population interacts with others in certain ways. These interactions give rise to a network of populations. Hence, an ecological community is composed of such population networks of various species interacting with each other within the same area. These biological, or biotic, components may also closely interact with non-living, or abiotic, components, forming an ecosystem. Ecosystems may be as small as the microbial communities inside the human...

In Microsoft Excel, plotting the mean along with standard deviation (SD) and standard error (SE) helps visualize data variability and reliability. To plot these values, follow these steps:
First, calculate the mean, SD, and SE of your data. The mean is obtained using the formula `=AVERAGE(range)`, while SD can be calculated with `=STDEV.P(range)` for a population or `=STDEV.S(range)` for a sample. SE is calculated as `=SD/SQRT(n)`, where `n` is the sample size.
To plot these values, use a bar...

Student's t-test in Microsoft Excel is a statistical method used to compare the means of two groups to determine if they are significantly different from each other. It's commonly used to evaluate hypotheses, such as testing whether a treatment has an effect compared to a control group. Excel provides built-in functions to perform t-tests, making it accessible for users needing to conduct basic statistical analysis.
To conduct a t-test in Excel, use the T.TEST function or the "Data...

Microsoft Excel is a powerful tool for statistical analysis, including calculating Pearson's correlation coefficient, which measures the strength and direction of a linear relationship between two continuous variables. Pearson's correlation coefficient, often denoted as "r," ranges from -1 to 1. A value close to 1 indicates a strong positive correlation, meaning as one variable increases, the other does too. A value close to -1 indicates a strong negative correlation, implying...