What are the best tests and statistics indicators for analyzing algae data?

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In summary, the conversation is about preparing a research report on the Macro alga in the Aqua maritime specialty. The issue is deciding which tests and statistics indicators to use in order to prepare a statistic tests plan and convince those responsible. The lab experiences involve studying two kinds of algae, Algae A and Algae B, in three different sites and with three different sexes. The observations are taken using SPSS and the goal is to compare and do tests according to different sexes per site and different sites per sex category. The observed IV count is over 100. In case study 2, the focus is on the number of spores produced by the algae in different temperature and luminosity levels. The question is which tests and statistics indicators to use
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moss888
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Hello,
I’m preparing a research report in Aqua maritime specialty; my case study concerns the Macro alga.
My case:
My issue is that there are a lot of tests procedures and statistics indicators those could be used so that I can’t figure out which tests should I take on consideration? Which tests should I avoid? My purpose is to prepare a statistic tests plan and statistics indicators set that explain well and convince the responsible.
My lab experiences:
Case study 1:
I’m studying two kinds of algae (http://en.wikipedia.org/wiki/Algae)
1. Algae A
2. Algae B
In three sites:
1. Site A
2. Site B
3. Site C
Those Algae are of sex:
1. Male
2. Female
3. Hybrid(Male and female at the same time like the snail)
The observations are taken in SPSS as follow:
Site Sex Month Quarter Weight
Possible values for the sites:
1 -> Site A
2 -> Site B
3 -> Site C

Possible values for the sex:
1->Male
2->Female
3->Hybrid
Possible values for the month:
1-> January
.
to
12->December
Possible values of the saison or quarter:
1->Harvest
2->Winter
3->Spring
4->Summer
Possible value of the weight
Could be a sacle numeric value with format like 000,00

The Observation concerns just one year (2008-2009)
The observed variable is the weight.
My Goal is to compare and do test according to each:
1. Different sexes per site or location
2. Different sites per sex category

The Observed IV (sample) count is more than 100

Case study 2:
I will study the number of the spore ( http://en.wikipedia.org/wiki/Spore) those are produced by the two same Algae.
First of all, each Algae is reduced to three sections
1. Inferior section
2. Intermediate section
3. Superior section
The fact is that each section produces different amount of spores, therefore we proceed and cut each Algae to three sections.
1. I studied this production in two different temperatures levels, namely 16 and 25 C.
2. I exposed them to different luminosity intensity level, whishes are tree levels
3. I also exposed them for different luminosity periods 12 hours per day and 6 hours per day
And I came out with different observations of spore numbers. I registered the number of the produced spore per week for six weeks.
Inferior section Intermediate section Superior section
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
What I’m asking is what is the suitable test set, which test should I avoid, which are the statistics indicators those could be used for each case study.
Thank you
 
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  • #2
A basic point to clarify is whether you are creating a plan for measurements that will be made in the future and trying to decide how to allocate resources (in statistics, this topic is called "The Design of Experiments") or whether you are preparing a plan to analyze data that has already been collected.

Statistics is a subjective field. If you need approval from certain people, the best thing to do is look up work that they have done and see what methods they have used.

There might be an algae biologist on the forum who happens to read your post and can tell you how to proceed, but I think the rest of us, the Wikipedia articles not withstanding, need to know what you are trying to find out from the data. Is this a "what factors influence..." type of analysis ?
 

1. What is the purpose of a test plan?

A test plan outlines the approach, scope, and objectives of a testing process. It serves as a guide for the testing team to ensure that all necessary aspects of the system are tested and any potential issues are identified and addressed before the product is released.

2. How do I determine which test plan to use?

The selection of a test plan depends on various factors such as the type of software being tested, the project timeline, available resources, and the level of risk associated with the software. A thorough analysis of these factors can help determine the most suitable test plan for a particular project.

3. What are the different types of test plans?

There are several types of test plans, including functional, integration, system, acceptance, regression, and performance test plans. Each type focuses on different aspects of the software and has its own set of objectives and testing techniques. It is essential to select the appropriate type of test plan based on the specific needs of the project.

4. How do I create a test plan?

To create a test plan, it is important to understand the project requirements and objectives, along with the scope of testing. The test plan should include a detailed description of the testing process, test objectives, test cases, and test schedule. It should also specify the roles and responsibilities of each team member involved in the testing process.

5. How often should a test plan be updated?

A test plan should be updated whenever there are changes in project requirements, objectives, or scope. It is important to review and update the test plan regularly to ensure it reflects the current state of the software and the testing process. Any changes made to the test plan should be communicated to the testing team to ensure everyone is on the same page.

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