What do you think will likely happen when a cell containing 1% sucrose is placed in an environment with 50% sucrose?
I would guess that the weigh of this experiment concentration will low the sucrose after they are mix togther.
I would also like you to consider the following terms as they relate to this experiment:
Tonicity: The ability of a solution to cause a cell to gain or lose water.
The tonicity of a solution mainly depends on its concentration of solutes that cannot cross the plasma membrane relative to the concentrations of solutes in the cell.
· Isotonic: An environment of equal solute concentration to the cell. In this environment, you will not likely see much of a change in cell size. Will water still move randomly across the plasma membrane?
I will guess that the water would moved randomly because every living cell exists in a liquid environment that it needs to survive. One of the most important functions of the cell membrane is to regulate the movement of dissolved molecules from the liquid on one side of the membrane to the liquid on the other side.
· Hypotonic: This term represents an environment that contains a lower solute concentration than the cell. In this case, water will move into the cell, the cell will swell and may burst. To test your knowledge from the last module, what cellular structure do plants have that will provide protection from burstinTop of Form 1
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Introduction to the Scientific Method
What is you favorite Skittles color? Do you sort your Skittles by color and eat one color at a time, or do you eat them randomly?
In the lab, students will use the scientific method to answer the question, “Can humans detect the color of Skittles based on taste alone?” Student’s work in groups of four, taking turns being ‘subjects’ of an experiment. The subjects are blindfolded and given Skittles, which they have to determine the color. Once all of the subjects have been tested, the students aggregate their data on the board and use statistics (an unpaired t test) to determine whether or not humans can detect the color of Skittles based on taste alone. A variety of unpaired t tests will be employed to determine whether humans can: 1) detect the color or Skittles (in general), and 2) detect specific colors of Skittles.
This lab is an extremely fun, yet comprehensive experience introducing students to the process of the scientific method.
The Scientific Method
The scientific method is a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge.To be termed scientific, a method of inquiry must be based on empirical and measurable evidence subject to specific principles of reasoning. The chief characteristic which distinguishes the scientific method from other methods of acquiring knowledge is that scientists seek to let reality speak for itself, supporting hypotheses when their predictions are confirmed and challenging hypotheses when its predictions prove false. Scientific researchers propose hypotheses as explanations of phenomena, and design experimental studies to test these hypotheses via predictions which can be derived from them. These steps must be repeatable, to guard against mistake or confusion in any particular experimenter. Theories that encompass wider domains of inquiry may bind many independently derived hypotheses together in a coherent, supportive structure. Theories, in turn, may help form new hypotheses or place groups of hypotheses into context.
Scientific inquiry is generally intended to be as objective as possible in order to reduce biased interpretations of results. Another basic expectation is to document, archive and share all data and methodology so they are available for careful scrutiny by other scientists, giving them the opportunity to verify results by attempting to reproduce them.
The Scientific Method Process
The overall process involves making conjectures (or hypotheses), deriving predictions from them as logical consequences, and then carrying out experiments based on those predictions to determine whether the original conjecture was correct. Though the scientific method is often presented as a fixed sequence of steps, they are better considered as general principles. Not all steps take place in every scientific inquiry (or to the same degree), and not always in the same order. Nevertheless, the basic formula of the scientific method is as follows:
The Scientific Method
The Scientific Method
The question can refer to the explanation of a specific observation, as in “Why is the sky blue?”, but can also be open-ended, as in “How can I design a drug to cure this particular disease?” This stage also involves looking up and evaluating previous evidence from other scientists and one’s own experiences. If the answer is already known, a different question that builds on the previous evidence can be posed.
A hypothesis is a conjecture, based on the knowledge obtained while formulating the question, that may explain the observed behavior of a part of our universe. The hypothesis uses a general understanding of nature to generate a specific prediction. Terms commonly associated with statistical hypotheses are null hypothesis and alternative hypothesis. A null hypothesis is the conjecture that the statistical hypothesis is false (e.g. A drug does nothing and that any cures are due to chance effects.). Researchers normally want to show that the null hypothesis is false. The alternative hypothesis is the desired outcome (e.g. The drug does better than chance.). Scientific hypotheses must be falsifiable, meaning that one can identify a possible outcome of an experiment that conflicts with predictions deduced from the hypothesis; otherwise, it cannot be meaningfully tested.
Predictions are logical consequences of the hypothesis. Ideally, the prediction must also distinguish the hypothesis from likely alternatives; if two hypotheses make the same prediction, observing the prediction to be correct is not evidence for either one over the other.
Scientists test hypotheses by conducting experiments. The purpose of an experiment is to determine whether observations of the real world agree with or conflict with the predictions derived from an hypothesis. If they agree, confidence in the hypothesis increases; otherwise, it decreases. Agreement does not assure that the hypothesis is true; future experiments may reveal problems. Experiments should be designed to minimize possible errors, especially through the use of appropriate scientific controls. For example, tests of medical treatments are commonly run as double-blind tests. Test personnel, who might unwittingly reveal to test subjects which samples are the desired test drugs and which are placebos, are kept ignorant of which are which. Such hints can bias the responses of the test subjects. Failure of an experiment does not necessarily mean the hypothesis is false. Most individual experiments address highly specific topics for reasons of practicality. As a result, evidence about broader topics is usually accumulated gradually.
Analysis of a well-designed experiment can either support or falsify hypotheses. The predictions of the hypothesis are compared to those of the null hypothesis, to determine which is better able to explain the data. In cases where an experiment is repeated many times, a statistical analysis such as a chi-squared test may be required. If the evidence has falsified the hypothesis, a new hypothesis is required; if the experiment supports the hypothesis but the evidence is not strong enough for high confidence, other predictions from the hypothesis must be tested. Once a hypothesis is strongly supported by evidence, a new question can be asked to provide further insight on the same topic. Evidence from other scientists and experience are frequently incorporated at any stage in the process. Many iterations may be required to gather sufficient evidence to answer a question with confidence, or to build up many answers to highly specific questions in order to answer a single broader question.
The goal of a scientific inquiry is to obtain knowledge in the form of testable explanations that can predict the results of future experiments. This allows scientists to gain an understanding of reality, and later use that understanding to intervene in its causal mechanisms (such as to cure disease). The better an explanation is at making predictions, the more useful it is, and the more likely it is to be correct. The most successful explanations, which explain and make accurate predictions in a wide range of circumstances, are called scientific theories.
Most experimental results do not result in large changes in human understanding; improvements in theoretical scientific understanding is usually the result of a gradual synthesis of the results of different experiments, by various researchers, across different domains of science. Scientific models vary in the extent to which they have been experimentally tested and for how long, and in their acceptance in the scientific community. In general, explanations become accepted by a scientific community as evidence in favor is presented, and as presumptions that are inconsistent with the evidence are falsified.
Scientific knowledge is closely tied to empirical findings, and always remains subject to falsification if new experimental observation incompatible with it is found. That is, no theory can ever be considered completely certain, since new evidence falsifying it might be discovered. If such evidence is found, a new theory may be proposed, or (more commonly) it is found that minor modifications to the previous theory are sufficient to explain the new evidence. The strength of a theory is related to how long it has persisted without falsification of its core principles.
Confirmed theories are also subject to subsumption by more accurate theories. For example, thousands of years of scientific observations of the planets were explained almost perfectly by Newton’s laws. However, these laws were then determined to be special cases of a more general theory (relativity), which explained both the (previously unexplained) exceptions to Newton’s laws as well as predicting and explaining other observations such as the deflection of light by gravity. Thus independent, unconnected, scientific observations can be connected to each other, unified by principles of increasing explanatory power.
Since every new theory must explain even more than the previous one, any successor theory capable of subsuming it must meet an even higher standard, explaining both the larger, unified body of observations explained by the previous theory and unifying that with even more observations. In other words, as scientific knowledge becomes more accurate with time, it becomes increasingly harder to produce a more successful theory, simply because of the great success of the theories that already exist. For example, the theory of evolution by natural selection explains how species adapt to their environments.
The scientific method is not a single recipe: it requires intelligence, imagination, and creativity. In this sense, it is not a mindless set of standards and procedures to follow, but is rather an ongoing cycle, constantly developing more useful, accurate and comprehensive models and methods.
Lab: Can you test the Rainbow
In this lab you will be utilizing the scientific method in order to address the following question:
· Can humans determine the color of Skittles® by taste alone?
1. If this is an online lab you will perform the following experimental protocol on yourself and one family member or friend at home. If this is a classroom lab, you will work with a group of four to complete this protocol.
2. Wash your hands with soap.
3. Each person will receive 3 Skittles® of each color (for a total of 15).
4. Blindfold the first subject.
5. The handler will remove the allotted number of Skittles® from the package and place them onto a paper plate. The subject should be blindfolded for this part so they can not see the colors.
6. The handler will give the subject one of the Skittles® and the subject will predict its color. The color must be chosen randomly!!!! If the color is correctly identified, it is deemed “correct.” If the color is incorrectly identified (or the subject can not identify the color), it is deemed “incorrect. ”
7. Record results in the tables in The Biology Lab Primer as tallies. For “ALL COLORS” simply add up the tallies of “correct” and “incorrect” for the subject.
8. Repeat 4-7 for the other test subject.
9. Record your results on the whiteboard (if a face-to-face class) or in the class discussion board of Blackboard® (if an online class) by the specified due date according to the instructions given to you by your instructor.
Each subject that you tested in your group is known as a replicate. The more replicates you include in your analysis, the more reliable your findings become. This is due to the fact that certain results can simply happen by chance. For example, if you flipped a coin twice and got heads both times, it does not mean you are certain to get a heads on a third coin toss. For this reason, we are going to collect as many replicates from the class as we have students. Fill in the table in The Biology Lab Primer with the results from the whole class, reported on the white board (in a face-to-face class) or in the discussion board of Blackboard® (if an online class).
As you conduct this experiment, you may feel that your hypothesis may or may not be supported (or you may get a lot of conflicting results). In order to summarize data of this nature, we use statistics. A common statistic is mean. However, simply calculating the mean of the two groups doesn’t tell us whether or not those two groups are “statistically significantly” different. For that we need a statistical test. For this analysis, we will be using a simple test known as an unpaired t test.
In our case the unpaired t test will compare the means of two groups. Our two groups are “correct” and “incorrect.” With this test, we will be able to determine whether or not the difference in the means of correctly identified Skittles® differs from incorrectly identified Skittles®. In other words, we will be able to determine whether or not we can discriminate among the Skittles® flavors based on taste alone.
1. Go to: http://www.graphpad.com/quickcalcs/ttest1.cfm
2. Under “1. Choose data entry format”, select “Enter up to 50 rows.”
3. Under “2. Enter data” you will input your data
o First change the label to correspond with the color of the Skittles® and the correctness of the result. For example, if you are testing the means of red Skittles®, label group 1 as “Red correct” and group 2 as “Red incorrect”.
o Input the data from those two columns only.
4. Under “3. Choose a test”, select “Unpaired t test.”
5. Under “4. View the results”, click on “Calculate now.”
6. Repeat steps 1-4 for each color (e.g. red, orange, yellow, green, purple), and for “ALL COLORS.”
If you have never taken a statistics class before, the results spit out by QuickCalcs (GraphPad Software, 2013) might be a little intimidating. Have no fear! We will just focus on the statistics that will answer our question.
The p value allows us to determine whether or not the means of the two samples are “significantly” different. When you take a statistics class, you will learn how this statistic is created. For our purposes, it is sufficient to be able to interpret this statistic without actually knowing how to calculate it.
The p value is the probability (ranging from zero to one), that answers whether or not the observed means of two populations (e.g. “correct” and “incorrect” in our study) are real and not merely a product of chance. In most biological studies, if the p value is less that 0.05 we can state that there is, in fact, a “statistical” difference between the two populations. This is somewhat of an artificial cut off, but it is one that is widely accepted in this field of study. Therefore, in our study if you get a p value less than 0.05, you can state that there is a “significant” difference between the “correct” group and the “incorrect” group for that color.
The mean is simply the average. If you find that there is a significant p value (p < 0.05), then the next step is to look at the means (Fig. 1). If the mean is larger for the “correct” group, this means that humans can identify that color by taste alone. If the mean is larger for the “incorrect” group, this means that humans can not identify that color by taste alone. If the p value is insignificant (p≥0.05), we assume there is no difference between those means. In other words, the results for our experiment are inconclusive for the ability for humans to discriminate color based on taste alone.
Example Result and Conclusion
Fig. 2 represents results that could be found in this experiment. It is comparing the number of correct versus incorrect identification of red Skittles based on taste alone. If we look at the p-value, it is less that 0.05 (0.02 = p < 0.05). From this statistic, we can conclude that there is a difference between the means of “correct” and “incorrect”. By comparing the means, we see that the mean “correct” is greater that “incorrect”. From this we can determine, with confidence that humans can determine the color of red Skittles based on taste alone.