Considering interactions between questions, hypotheses, and data is therefore critical when designing research. Note the gray line in the diagram above indicates that the process is reversible, allowing full consideration of the interdependencies between questions, hypotheses, and data. A series of questions that illustrate both directions of this process could look like this:. This process ensures that questions, hypotheses, and data all match.
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Note that this exercise is about identifying the kind of data that can be used to statistically distinguish hypotheses, not selecting data a priori that will be consistent with i. Going through several iterations of the process before identifying good questions and hypotheses is a realistic expectation.
Proposals market your research, to your committee or to a funding agency. As such, they must present your proposed research clearly and compellingly. Selling great research ideas effectively is largely about organization. A proposal needs to walk the reader from the conceptual context for your research to how you will test hypotheses within that context.
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The flow from concepts to methods needs to be clear and logical throughout the proposal. After reading your proposal, the reader needs to understand your research questions, why you are asking them, why your hypothesized answers are credible, that your methods offer a strong likelihood for meeting your objectives, and finally that your research will produce new and interesting results.
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All of this must be accomplished in a very limited amount of space. Organization to achieve this end can be envisioned as a funnel that progressively leads the reader from the general to the specific:. All ecological research takes place under a conceptual umbrella. For example, a survival study takes place under the conceptual umbrella of demography. It is hard to understand why a survival study should be done without knowing something about its ecological importance.
You do not want to get too big or too obvious in this but get to the point: what is the immediate context needed to understand why you are doing your research? Importantly, this material needs to go beyond your study species. Example: a variety of factors can limit growth of animal populations. Most ecological concepts have already been addressed through research of one form or another. A summary of this work can A familiarize the reader with current ideas relevant to your research, and B ultimately make clear how your research will add to it.
Again, this presentation should not be specific to your study species. Orient the reader to your study system i. Here is where you justify the purpose for your study and it should be convincing. Example: fox population X is declining but the causes are unknown. State your research questions, having walked the reader from the general ideas behind your work to an application of those ideas to your study system. When you state your questions, the reader should understand what led up to them and that they are important and need to be answered.
Example: What factors are causing the decline of fox population X? Present the hypotheses you have chosen that represent interesting and plausible answers to your questions. Like the questions, they should have been well justified before this point. For example: Decline of fox population X could be due to loss of habitat, increased predation, declining prey populations… etc. State predictions of ecological patterns you would expect to see for each hypothesis, based on the assumption it is true. Example: prey populations are most important to survival of foxes would predict survival will be highest in areas with the most prey.
Note that the prediction is in the form of a numerical relationship, i.
Although hypotheses and predictions are shown separately in the diagram, the most effective presentation usually pairs each hypothesis with its prediction. State the methods you will use to collect the data for your hypothesis tests. Example: I will obtain historical data on abundance of fox population X, changes in landcover, prey density, predator density … etc.
State the analytical methods you will use to test your hypotheses.
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Every analysis needs to tie explicitly to a hypothesis test, in the same order hypotheses were presented in the introduction. A common temptation is to present methodological steps sequentially, which can be confusing because connections to hypothesis tests become unclear. Avoid presenting any results in this section. Example: I will use multiple linear regression to evaluate the correlations between abundance of fox population X and percent availability of suitable habitat, density of prey, density of predators… etc. If you have done a good job with your funnel then organizing a paper is surprisingly easy.
The funnel for your proposal provides the foundation for the first half of your paper, sometimes with only modest changes needed. To add your results and discussion just flip the funnel, i. The results section should be organized identically to your methods section, according to your research questions and hypothesis tests, under the same subheadings.
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Writing a discussion is very difficult after being immersed in data collection and analyses. Even experienced scientists can struggle to broaden their perspective enough to interpret their results well, at least at first. Allowing other researchers that do not share your research focus to read and critique your writing can help a lot. Give a broad overview of the data you collected, e.
State the results of your statistical tests. These should be very concise and factual.
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Do not interpret results here, save that for the discussion. Your statistical results represent tests of your hypotheses, either supporting them or refuting them. Those results have implications for the biological arguments you used to justify your hypotheses, here is where you discuss them. If your results do not support a hypothesis, what does it mean for the biology behind it? What does it mean if your results do support it?
Interpret each hypothesis test in the same order as hypotheses, methods, and results are presented throughout the paper. Conclude with a synthesis on the biological implications of all of your hypothesis tests combined—how do the results of your hypothesis tests answer your research questions? Example: My hypothesis that habitat loss has resulted in the decline of fox population X was supported.
Foxes in population X are likely limited by prey availability, but other possible causes cannot be ruled out. My hypothesis that predation of foxes has produced the decline was falsified, suggesting Scale up from the animals you sampled to your study system. What biological inferences for can you draw for your ecological system based on your hypothesis tests, e. A note of caution: your interpretations now extend beyond your data set and are hypothetical.
You need to present them as hypotheses, not conclusions. These new images were then fed back into the training algorithm to further update and improve the program. The resulting system identifies the location of giraffe torsos in images with a very high accuracy, even when the giraffe is a small portion of the image or its torso is partially blocked by vegetation.
It used to take us a week to process our new images after a survey, and now it is done in minutes. This system moves us closer to fully automatic animal identification from photos. The new system will dramatically accelerate Lee's research on giraffe populations, which have rapidly declined across Africa due to habitat loss and illegal killing for meat. This process will also be useful to researchers studying other animals with unique identifying patterns--including some wild cats, elephants, salamanders, fish, penguins, and marine mammals.
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