Common Errors

10 Common writing errors:

While grammar and spelling is slightly less important than the science you are presenting, a report rife with errors makes your reader question your science; sloppy presentation indicates sloppy science.

If you have trouble with any of the following errors, look them up!

  • Affect / Effect
  • It's / Its
  • Then / Than
  • There / Their /They're
  • Preform / Perform
  • Sentence fragment
  • Run-on sentence
  • Comma splice
  • Semicolon use
  • Weak paragraphing (paragraphs that have no clear topic or that try to address more than one point)

Also remember:
The word "data" is plural, so make sure any verb you use with data as a subject is also plural. The data shows (incorrect) vs. The data show (correct)

10 Common lab report mistakes

Mistake #1: Writing the entire report the night before it is due.

There are two problems with this approach. The first is that after a week you will have forgotten much of what you did in the lab. The second problem is you will have no time to reflect on what you have written and you will essentially be handing in a first draft. At the very least, complete the analysis of the results and write the materials and methods within a day or two of your lab.

Mistake #2: Writing a report with no clearly defined purpose in mind.

A study’s central scientific purpose will supply direction to the entire report. It is not possible to write a clear introduction if you have no idea what the purpose of your study was. Similarly, the discussion will have no focus if you are not clear on what you were trying to determine. Even the results section will be easier to put together if you know the central question you wanted to address. See Introduction for more information.

Mistake #3: Writing the report in the order it is presented.

If you attempt to start with the first sentence of the introduction and end with the last line of the discussion you will not only end up with a poor quality product but you will probably spend more time writing than is necessary. We always recommend you start by analyzing the results (as soon as possible after completing the study). You could tackle methods first or simultaneously but you cannot write an introduction or discussion until you clearly understand what happened in your study and what it means.

Mistake #4: Including information that is not directly related to the study being presented.

This happens most frequently in the introduction and the discussion. Remember, when writing a scientific paper you are not writing a mystery novel. Your reader should not need to sift through mountains of superfluous details to understand what you did, why you did it, what you found and what you think it means.

Mistake #5: Confusing analysis and interpretation (i.e. mixing up results and discussion).

This is probably the toughest concept to deal with because the word "interpretation" is frequently used to mean both "analyze the data" and "propose what the results mean".

Pointing out a trend in the data is not interpretation, telling the reader what the trend means is interpretation.

Test any statements you are making in the results as follows:

See here for more information.

Mistake #6: Presenting raw data in the results and/or not using visuals in the results.

Rarely is raw data useful for drawing scientific conclusions. Instead, data must be analyzed with the goal of answering specific questions. The analysis may take many forms, such as graphing or tabulating, to examine relationships or reveal trends. Fully analyzed data is presented in the Results and it is your job to make sure your reader can easily see important trends. Highlighting trends will require you to use actual sentences.

Each visual needs to be used in the results; that is, you need to make a statement that addresses each visual. Additionally, each visual included needs to directly address your purpose (i.e. avoid putting in visuals just because they look "pretty").

See Verbalizing the Results.

Mistake #7: Not putting statements in the results.

While visuals will be an important aspect of the results section, you must actually tell the reader, in words, what the key results are. You conducted your study with a particular purpose in mind. In the results you need to clearly address the purpose with actual statements.

See Verbalizing the Results.

Mistake #8: Presenting the same result in two or more ways.

Present the same data only once. If you want to use a visual, use only one (i.e. choose a table or a figure).

We have noted previously that if you do use a visual, you will need to "introduce" it in the text portion of the results and point out the major result(s) shown in the visual. However, if you repeat every detail of the visual in the text, you are actually presenting the same data twice.

Remember: If you can easily state the result in a single sentence, then it might not need a visual at all (not all results have to be presented as visuals).

Mistake #9: Writing a discussion that has no interpretations.

When you interpret results you are explaining what the results mean. Interpretation includes: explaining how the results relate to the study’s purpose, discussing the meaning of unexpected or unusual results, making suggestions for further studies, making suggestions for improving the current study, and relating the results to the general understanding of the field. See Discussion for more details.

For example, if you found that measurements made with your pipetter were not 100 percent accurate, what does that mean for experiments conducted using this measuring device?

Also remember:
When making suggestions for further studies, be more specific than just saying:
I would repeat the study with a larger sample size. Beware of suggesting studies that are too vague, that are not related to the current study, or that are not doable using current technology.

Mistake #10: Assuming unexpected or unusual results are due to human error.

Unusual and unexpected results are what make science so interesting. When considering unexpected results, assume that you collected representative data and look for biological/scientific explanations for what you see. You will know you are on the right track if you can think of ways to test your interpretations further.


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