This is not an exhaustive list. With every new lab protocol, you folks come up with the darnedest ways of messing up a perfectly good paper. However, if you heed the comments here your reports stand a much better chance of being mistaken for professionally written research papers.
Use of the wrong verb tense, at best, is irritating to read and reflects poorly on the student's writing skills. At worst, the reader can be confused as to what facts are already known and what was newly discovered in the actual study that is the subject of the paper. As a rule, use past tense to describe events that have happened. Such events include procedures that you have conducted and results that you observed. Use present tense to describe generally accepted facts.
We sought to determine if mating behavior in Xiphophorus helleri is related to male tail length by placing combinations of two male fish with different length tails in the same tank with a female fish.
We found that protein synthesis in sea urchin embryos treated with actinomycin D was considerably less than in untreated embryos. This finding agrees with the model stating that protein synthesis in 24 hour sea urchin embryos is dependent on synthesis of new messenger RNA.Reference to results of a specific study should also be in past tense.
Abercrombie and Fitch reported that 30% of the public is allergic to wool.Mixing tenses is even worse - this sort of thing hurts my ears. Unfortunately, the people who read the news in television and radio broadcasts are frequently unaware of verb tense at all.
Two guys rob a liquor store downtown. The robbery occured at midnight last night.The last one had me puzzled. I was thinking, if they know the inmates are in the trailer, why don't they just go in and get them? What the article actually reported was that the two had hidden in a trailer which was driven out of prison, allowing them to escape. I grew up speaking and reading English (the American version, that is). Imagine the difficulty faced by a non-native speaker who learns proper English and then reads the local rag or tries to make sense out of reports by "talking heads" on new shows.
[from a newspaper article] Two inmates hide in trailer to escape S.C. prison.
Incomplete sentences, redundant phrases, obvious misspellings, and other symptoms of a hurriedly-written paper can cost you. Please start your work early enough so that you can proofread it. Check spelling of scientific names, names of people, names of compounds, etc. Spelling and grammatical errors can be embarrassing. Since many very different terms have similar names, a spelling error can result in a completely incorrect statement.
When you print off your paper, please make sure that tables are not split over more than one page, that headings are not "orphaned," pages submitted out of sequence, etc. Remember, someone has to read this thing! If the reader is an editor or reviewer, you might get a rejection notice because you were too sloppy.
A research paper summarizes a study. It does not identify who did what. Reference to instructors, fellow students, teams, partners, etc. are not appropriate, nor is it appropriate to refer to "the lab."
If you state facts or describe mechanisms, do so in order to make a point or to help interpret results, and do refer to the present study. If you find yourself writing everything you know about the subject, you are wasting your time (and that of your reader). Stick to the appropriate point, and include a reference to your source of background information if you feel that it is important.
Including material that is inappropriate for the readership
It isn't necessary to tell fellow scientists that your study is pertinent to the field of biochemistry. Your readers can figure out to what field(s) your work applies. You need not define terms that are well known to the intended readership. For example, do you really think it is necessary to define systolic blood pressure if your readership consists of physicians or cardiovascular physiologists?
Technical writing differs from the writing of fiction, opinion pieces, scholarly English papers, etc. in many ways. One way is in the use of superlatives and subjective statements in order to emphasize a point. We simply do not use such writing styles in science. Objectivity is absolutely essential.
Subjectivity refers to feelings, opinions, etc. For example, in your discussion you might write, "We felt that the fixative was bad, because we had difficulty finding flagella on our Chlamydomonas." Another researcher is unlikely to risk time and resources on the basis of your "feeling." On the other hand, you might write, "The percentage of cells with flagella was inversely proportional to the time they spent in fixative, suggesting that the fixative was causing cells to shed flagella." This is information that another scientist can use.
Superlatives include adjectives such as "huge," "incredible," "wonderful," "exciting," etc. For example, "the mitochondria showed an incredibly large increase in oxygen consumption when we added uncoupling agent." Your definition of incredible might be different from that of someone else - perhaps a five fold increase is incredible to you, but not for the next person. It is much better to use an objective expression, such as "Oxygen consumption was five fold greater in the presence of uncoupler, which is a greater change than we saw with the addition of any other reagent."
Similarly, we don't write that we believe something. We present the evidence, and perhaps suggest strong support for a position, but beliefs don't come into play. In particular, we do not "expect" a particular set of results, or "wire" a hypothesis so that it appears that we correctly predicted the results. That sort of practice is another example of lack of objectivity.
See my essay on fact, hypothesis, and theory. The requirements for scientific proof are extremely rigorous. It is highly doubtful that any single experiment can be so well controlled that its conclusions can be regarded as proof. In fact, for any result to be accepted it must be confirmed independently. In fact, we can never know if a model as we describe it presents an accurate picture of any natural process. We can never look at the original blueprint to check our conclusions. So... your data may strongly support a position, or they may allow you to reject a hypothesis, but they aren't likely to provide anything close to proof.
Please avoid obvious grammatical errors. Granted, you aren't writing an English paper (heck, an English teacher would tear my own writing style to shreds). However, clear written communication requires proper sentence structure and use of words. Make sure that your sentences are complete, that they make sense when you proofread, and that you have verb/subject agreement.
Spelling errors in a paper make you look amateurish. For example, absorbance is read from a spectrophotometer. You don't read absorbencyfrom a spectrometer. Worse, they can change the entire meaning of your writing. One letter changes the chemical compound you describe. I know the action of cycloheximide in eukaryotic cells, but I do not know the action of cyclohexamide.
Changing temperature had the following affect on the subject.'Affect' is a verb. 'Effect' is a noun. What happened to the subject was an effect. The temperature change affected the subject. Please learn the difference.
The data lead to the assumption that x has no relationship to y.If you base a conclusion on data, then your conclusion is a deduction, not an assumption. In fact, in experimental science assumptions are usually avoided. A purpose of controls is to eliminate the need to assume anything.
Our inability to ensure that all cells in the population were in the same stage of development skewed our data.This statement doesn't reveal very much. The writer intended to say that the data points were more scattered, that is, the non-uniformity of the population resulted in unacceptably high experimental error. The word 'skew' means 'having an oblique position; turned or twisted to one side; slanting; sloping.' It can be used as an adverb or noun as well. In statistics, the word refers to an asymmetric distribution of data. Nowhere in the definition is there any reference to the state of being incorrect or more scattered. Thus, not only is the word overused, it is also misused.
We rationalized the finding that blocking the sodium pump had no affect on uptake of glucose by suggesting that the symport mechanism depends solely on the sodium gradient, which persists long after the pump is shut down.A definition of 'rationalize' is 'to explain or justify.' Another is 'to attribute logical or creditable motives to actions that result from other, perhaps unrecognized, motives.' In short, to make excuses. As I learned in English class a long time ago, the term's principal usage is to attempt to justify something on dubious grounds. For example, 'he rationalized his poor behavior by saying that he had just broken up with his girlfriend and was distraught.' The definition does not include anything about the explanation being valid, therefore another word would be preferable. Try
A likely explanation for the finding...is that...The word 'data' is plural. However since investigators usually refer to sets of data, there is a tendency to use the word as though it was singular. Hence a writer will state, 'the data was affected by the phase of the moon,' or 'the data suggests that phase of the moon has no effect on mood.' As awkward as it may seem to you, the proper phrases are, 'the data were affected...,' and 'the data suggest...' By the way, the singular form is 'datum.'
We used a spectrophotometer to determine protein concentrations for each of our samples. We used an oscilloscope to measure resting potentials in crayfish muscle.
The spectrophotometer or oscilloscope may be a novel, mysterious, and versatile device to you, but I suspect that even an expert biochemist would have a hard time finding a protein concentration using only a spectrophotometer. The first statement leaves out the dye reagent, standards, pipettors, etc. that are required to perform the assay. The second statement omits any reference to the micropipets or the specialized electronic instrumentation that is required in order to measure transmembrane potentials.
What information did you intend to convey? If you intend to describe the methodology, then write a complete description. If you intend only to summarize the procedures then you might seek a phrase that sums up what was done without oversimplifying. For example, "We used a colorimetric assay to determine protein concentrations in each of our samples." Or, "We measured resting membrane potentials using KCl-filled micropipets with a microprobe system from [supplier and/or reference].
The purpose of a discussion is to interpret the results, not to simply state them in a different way. In most cases a superficial discussion ignores mechanisms or fails to explain them completely. It should be clear to the reader why a specific result came to pass. The statement, "The result agreed with the known theoretical value," tells us nothing about the mechanism(s) behind the result. What is the basis for expecting a particular result? Explanations may not be easy and your explanation may not be correct, but you will get most or all of the available credit for posing a reasonable explanation, even if it is not quite right. Superficial statements, on the other hand, will cost you.
Sometimes you cannot easily find the right wording in order to explain a cause and effect relationship, or you may not understand the concept well enough in order to write an explanation. Anthropomorphism is a type of oversimplification that helps the writer avoid a real explanation of a mechanism. A couple of examples should make the point for you.
Sodium wants to move down the chemical gradient toward the compartment with the lower concentration.
The thought behind the statement is correct, but the statement does not represent the correct mechanism. Sodium has no free will. It tends to move toward the compartment with lower concentration because the probability of a sodium ion moving through a channel on the more concentrated side of the membrane exceeds the probability that an ion will move through a channel on the less concentrated side. If you don't want to explain the principle behind osmosis, you can simply state that osmotic pressure tends to drive sodium from the more highly to less highly concentrated side of a membrane.
The ETS works furiously in a vain attempt to restore the chemiosmotic gradientWow. Well, the adverb "furiously" is not only subjective, but it normally applies to a deliberate action. We know that the ETS (electron transport system) is a set of carrier complexes embedded in a membrane, and that it cannot be capable of a deliberate action. Something that cannot act deliberately cannot think, either. There is a physical cause and effect relationship between the ETS and the chemiosmotic gradient that does not require attributing a free will to any part of the system.
Converted data are data that have been analyzed, usually summarized, and presented in such a way that only the information pertinent to the objectives of the study is presented. Raw data refers to results of individual replicate trials, individual observations, chart records, and other information that comes directly from the laboratory.
Once you have presented converted data, do not present the same data in a different way. For example, if the data are plotted, then don't include a table of data as well. Present a figure (such as a graph) if appropriate. If the data are better represented by a table, then use a table. The caption with any figure or table should include all pertinent information. One should not have to go into the body of the paper to find out the results of statistical tests on the data, or the rationale behind a curve fit.
Raw data are not usually included in your results. Raw data include lists of observations, meaurements taken in order to obtain a final result (e.g., absorbance, relative mobility, tick marks on a microscope reticule).
Use an appropriate number of decimal places (if you need decimal places at all) to report means and other measured or calculated values. The number of decimal places and/or significant figures must reflect the degree of precision of the original measurement. See our analytical resources for information on uncertain quantities and significant figures. Since the number of significant figures used reflects the level of precision of the measurement or calculation, there is never any need to qualify a measurement or calculation as 'about' or 'approximate.'
Graphs and other pictures that represent data are called figures, and are numbered consecutively. Tables are distinguished from figures, and are numbered consecutively as well. For example, a paper with two graphs, a reproduction of a segment of chart record and two tables will have figures 1, 2, and 3, and tables 1 and 2. Do note that I distinguished graphs from chart records. Not everything with gridlines is a graph. Graphs are analytical tools. Chart records are raw data (which may be presented in results as an example, if appropriate).
Do not draw conclusions in the results section. Reserve data interpretation for the discussion.
We have a statistically significant difference when analysis yields a very low probability that the difference was due to sampling error (random error) alone. If sufficient data are collected, and statistical significance is not achieved, the investigator can conclude that the null hypothesis is supported ñ there is no significant difference.
Lack of a significant difference does not mean that the result itself is insignificant. A finding, for example, that there are no intrinsic differences in fundamental mathematical ability among racial groups would be a very significant finding. Significance in this study refers to the importance of the result. "It is significant that we found no significant differences among the groups studied" is a valid, though perhaps confusing, statement.
There is a tendency among students to reject a study as inconclusive just because no statistically significant differences were found. Such rejection suggests a misunderstanding of the scientific method itself. You can conclude something from even the most poorly designed experiments. In fact, most well-designed experiments result in support for the null hypothesis. Be prepared to interpret whatever you find, regardless of what you think you should find. The purpose of experimental science is to discover the truth - not to make the data conform to one's expectations.