Wednesday, November 4, 2015

Describe the meaning of analysis, synthesis and scientific method in chemistry, using keywords such as hypothesis, hypothesis testing, theory,...

In general when you analyze something, you study it and all of the components which make it up. In chemistry, you break down a substance into its constituent elements. For example, consider water, H2O. When you do a chemical analysis on water you break down the substance (water) into what is combined to make it, two hydrogen molecules and one oxygen molecule. 

Now, synthesis is when you create something. In chemistry, synthesis is when you combine simple components, such as two hydrogen molecules and one oxygen molecule, to create a more complex substance, like water. Synthesis can be much more complex and can involve breaking chemical bonds to form more complex bonds or adding more molecules to an existing substance. For example, if you add another oxygen molecule to water, it becomes H2O2 which is an entirely different substance.


The scientific method is something which has been generally agreed upon by scientists worldwide. Attached is a helpful diagram illustrating the thought process of the scientific method. It goes something like this:


-Observations: You see, experience, or read something which sparks a question. You then take that question and wonder more about it. For example, you notice that you are thirsty after exercise but soda does not satisfy your thirst. Why?


- Formulation of a hypothesis: A hypothesis is your general prediction about the question that you want to test. For example, a hypothesis about the question of why soda does not quench your thirst could be: "Soda cannot quench my thirst after exercise because it has a high sugar content."


- Develop a testable prediction: A hypothesis must be something which can be tested, verified, or even falsified by others. For example: "Soda does not rehydrate as well as chocolate milk, which does not rehydrate as well as water." Such a statement is testable, unlike a hypothesis such as: "Soda does not hydrate after exercise because I am drinking the wrong brand."


- Experiment: Here is where you put your hypothesis to the test. For example, after doing the same exercise have three of your friends drink the same soda, three others drink chocolate milk, three drink water, and three drink nothing. Record their reactions, feelings, and physical and mental states. Repeat the exercise again with the same friends drinking the same liquid. Repeat again and rotate so that those who drank soda now try water, those who drank chocolate milk now drink soda, those who drank water now drink the chocolate milk, those who drank nothing drink something, etc. Repeat again, until every person has done the exercise with each liquid (or lack of liquid) afterwards. 


-Documentation: Always record your data through all parts of the experiment. After the experiment compile the data using appropriate models, including quantitative and qualitative analysis. Examine the data to see how well it supports or refutes the hypothesis.


Quantitative analysis is the examination of the amount or percentages of one or more constituents of a sample. For example, data of the average blood pressures of your friends after exercise is an example of a quantitative analysis. Quantitative analysis always deals with numbers. (http://www.britannica.com/science/quantitative-chemical-analysis).


Qualitative analysis involves the identification and describing of elements present in a sample that cannot be measured by numbers. For example, how thirsty your friends felt after the exercise could be qualitative analysis, with statements like "after consuming soda after exercise I was very parched. When I consumed chocolate milk after exercise I was only slightly thirsty." (http://www.britannica.com/science/qualitative-chemical-analysis).


-Conclusion: This is where you present your complete hypothesis, whether or not you can make a conclusion about your hypothesis, a concise summary of your experiment, and anything which might be done better or differently next time. 


Generally, if you take the separate definitions of reliability, validity, development, and limitations and apply it to a given model you should be able to better understand the model. 


Take your hypothetical soda experiment for example. If you conducted this with twelve friends of presumably similar age, gender, athletic ability, race, etc., your experiment is limited because of the lack of diversity and adequate sampling size. Your development of models in your documentation may be accurate, yet limited. Validity tends to be determined by others and how your experiments and results might be reproduced. However, if you used a large sample size, like 12,000 people, such sampling might be implicitly deemed valid. Reliability depends on the ability of the results to be reproduced by others.


I hope this helps!

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