Biology Trouble: Choosing Between Student's T-Test & Chi-Square Test

[aleferesco]

Homework Statement

Ok the main problem is that I don't really understand in which biology-related scenarios I'm suppossed to use the student's t-test or the Chi-square test (we are using these tests in my biology class)?

How do you know which test to use to analyze the following data and why?

1) the number of caterpillars found foraging on two different plant species

2)The body weight of fish in low vs high nutrient habitats

3)the height of plants which receive two different fertilizer treatments


2. Homework Equations and the attempt at a solution

I know the definition of these two tests

the students t-test is defined as a statistical test that compares the means of two samples and assesses wheter or not they differ enough to represent samples from different populations

the chi-square test is defined as a test that is used to test a hypothesis in an experiment in which the data are frequency data, rather than continuous data.

but I cannot make sense of these definitions. When I'm given questions regarding to identifying the type of test I would use to analyze some data I don't know which test to use.


I attempted to answer the 3 questions by thinking of them this way, use students t-test when data is continuous (and data is continuous when we talk about height, weight ) and use the Chi-square test when data is discrete (such as the number between two particular species).

but I'm not too confident with this, please explain on how you would do this

thanks

 

[nate808]

Thank you for your question. it is important to understand which statistical test to use in different scenarios. Both the student's t-test and the chi-square test are commonly used in biology-related experiments, but they serve different purposes.

The student's t-test is used to compare the means of two samples and determine if they are significantly different from each other. This test is appropriate when the data is continuous, such as in the case of body weight of fish in low vs high nutrient habitats. In this scenario, you would use the t-test to determine if there is a significant difference in body weight between the two groups of fish.

On the other hand, the chi-square test is used to test for differences in proportions or frequencies between two or more groups. This test is appropriate when the data is discrete, such as in the case of the number of caterpillars found foraging on two different plant species. In this scenario, you would use the chi-square test to determine if there is a significant difference in the number of caterpillars between the two plant species.

For the third scenario of height of plants receiving different fertilizer treatments, either test could potentially be used. If the data for plant height is normally distributed and continuous, the t-test would be appropriate. However, if the data is not normally distributed or is discrete (e.g. height categories), the chi-square test would be more suitable.

In summary, the key factor in determining which test to use is the type of data you are working with. Continuous data should be analyzed using the t-test, while discrete or categorical data should be analyzed using the chi-square test. I hope this explanation helps you better understand when and why to use these tests in biology-related scenarios.

Best of luck in your studies!

 

[Blueshift5]

As a biologist, it is important to understand the different statistical tests and when they should be used. In order to determine which test to use for a particular set of data, it is important to first understand the type of data being analyzed.

1) For the number of caterpillars foraging on two different plant species, the Chi-square test would be appropriate. This is because the data is discrete, meaning it can only take on certain values (whole numbers in this case). The Chi-square test is used to analyze categorical data, such as counts or frequencies. It will determine if there is a significant difference between the observed and expected values for each category (in this case, the number of caterpillars on each plant species).

2) For the body weight of fish in low vs high nutrient habitats, the Student's t-test would be appropriate. This is because the data is continuous, meaning it can take on any value within a range. The t-test is used to compare the means of two samples and determine if they are significantly different. In this case, we would be comparing the average weight of fish in low and high nutrient habitats.

3) For the height of plants receiving two different fertilizer treatments, the Student's t-test would also be appropriate. This is because the data is continuous (height can take on any value within a range) and we are comparing the means of two samples (plants receiving different fertilizer treatments).

It is important to carefully consider the type of data and the question being asked in order to determine the appropriate statistical test. Additionally, consulting a statistician or using statistical software can also help in selecting the correct test for your data.