Comparing two sets of data: multiple time points

In summary, the person is asking for advice on how to compare two groups (control and treatment) for statistical significance when collecting data at multiple time points. They are assuming that the data involves reaction or growth rates and are looking for a probabilistic model with a parameter that can be used to compare the two groups. They are asking for more specific advice on the model in order to make a recommendation.
  • #1
prime-factor
77
0
I am trying to compare two groups (for statistical significance), a control and a treatment group across more than one time point, for a single variable. For example

Control Treatment
0 sec x x
5 sec x x
10 sec x x
15 sec x x
20 sec x x
30 sec x x

What sort of test can I use to compare these two groups for statistical significance, given the number of time points?
The data was collected every five seconds during a 30 second period.
 
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  • #2
You haven't given enough information to get good advice. I'll assume you are doing something involving reaction rates or growth rates, since you've made some other posts about growing bacteria.

To do statistics, you must make enough assumptions to compute probabilities. I assume that people have invented probabilistic models for bacteria growth. Let's hope that they've invented one that has some single parameter lambda in it. Then one idea is to look at the probability of getting the observed differences in your two sets of data on the assumption that lambda is the same for both the treatment and control group. I assume you know more about models for bacterial growth rate that I do. If you can state one then perhaps I (or someone else) can make a more specific suggestion.
 

What is the purpose of comparing two sets of data with multiple time points?

The purpose of comparing two sets of data with multiple time points is to identify any patterns or trends that may exist over time. This can help to understand how the data changes and potentially make predictions about future data.

How do you choose which statistical test to use when comparing two sets of data with multiple time points?

The choice of statistical test will depend on the type of data being compared and the research question being addressed. Some common tests for comparing two sets of data with multiple time points include ANOVA, repeated measures ANOVA, and linear mixed models.

Can you compare two sets of data with different time intervals?

Yes, it is possible to compare two sets of data with different time intervals. However, it is important to account for any differences in time intervals when analyzing the data. This can be done by using a statistical method that allows for unequal time intervals, such as linear mixed models.

What are some potential limitations of comparing two sets of data with multiple time points?

One potential limitation is that the data may not be collected at regular intervals, which can make it more difficult to detect patterns or trends. Additionally, there may be other factors that influence the data over time, making it difficult to determine the true cause of any changes observed.

How can visualizations be used to compare two sets of data with multiple time points?

Visualizations, such as line graphs or scatter plots, can be used to compare two sets of data with multiple time points. These can help to identify any patterns or trends over time and make it easier to interpret the data. They can also be useful for communicating the results of the comparison to others.

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