Introduction- Research Question
• Goal – Inform the reader of the significance, relevance and purpose of your experiment. It should also provide any and all relevant
background info, so the reader can understand what you’ve done.
• Your research question should describe the scope of your laboratory, no more and no less.
• Needs to describe the scope of your lab. Should include your IV, your DV, and how you measured your DV.
• Some Sample Formats:
• How does Y affect X as measured by Z
• What is the rate of Y in various X, as measured by Z
Introduction- Background
• Background - Informs the reader of all relevant information they
might need to understand your lab. If you had to learn it/look it up, include it. Assume you have a 10th grade audience.
• You must include citations in this section
Considerations
Comes in three parts. They are all things you needed to think about before and while designing your lab. Talk about how these considerations shaped
your methods
• Safety– How did you ensure the safety of you and your group during the
lab. What precautions did you take? PPE?
• Environmental- How did your lab impact the environment. How did you
ensure that impact was positive (or minimally negative)
• Ethical*** What moral or ethical issues did you take into account while
planning/conducting the lab.
• Scarce resources Animals
Introduction Common Mistakes
• No citations
• Too broad a research question
• Not describing in your RQ how the Dependent variable was measured
• Skipping Considerations
• Shallow Personal Engagement /Not being specific enough
Methods- Variables
• Experimental Variables Explicitly state your Independent Variable and Dependent Variable.
• Controlled Variables – Describe What you kept the same across all
trials and all manipulations. Describe How you kept it the same, and WHY you kept it the same. Best practice is to use a 3 column table. Should have about 10 controlled variables
What How Why
Size and shape of paper towel used
Each trial used 1 flat sheet of paper towel, measuring 6 cm by 6 cm.
Methods – Procedures and Common
Mistakes
• A detailed description of what was done to carry out the lab. Should allow the reader to do the lab without you. Make sure to include at least one set up figure, and at least one action figure.
(Figure = picture or drawing)
• Methods Common Mistakes
• Not getting clarification on Independent Variable and Dependent Variable
• Forgetting the “why” in your C.V.
• “Fluff” CV’s
Results- Raw Data
• Goal – Display data in the clearest way possible, and walk reader through your data processing. You will also be evaluating the accuracy and precision of your data through uncertainty values
• Raw Data Relevant data that has had “no math” done to it. All your measurements in here should have Absolute Uncertainty evaluating them. If you have lots of raw data but you don’t need to look at all of it, place extra tables in the appendix
• 2 Types of Raw Data.
• Qualitative(Observations) – Describe anything in the lab that you feel may impact the answer to your RQ. Only describe something you could not describe with numbers.
Results- Data Processing
• Use a combination of narrative and “shown work” (math) to describe how you took your raw data and made it processed data. Ex: Taking an average. Always show the general equation and at least one
example.
• Based on the type of math you are doing you will need to select what type of uncertainty calculations are best to use. You will need to show your work for these calculations as well.
Data Processing Rationale
Show the equation and “work” for each math process that you do. You only need to show your work once for each math process that you do.
Results – Processed Data
• Processed Data
• Data after you have done your math. For example, Averages of Data, or % change in mass. You should always have tables, and you should always
have some kind of graph. This data should be used to support claims made about your Research Question in your conclusion section. This section
should include your propagated uncertainty. Graphs
• Title – have one
• Axis – have them
• Labels – use them
• Error Bars- use your uncertainty values to make them
Purpose of Uncertainty
• The tools we use are not perfect, and we need to keep track of those imperfections when we carry out investigations.
• Uncertainty essentially tells us how much trust we should put into the data points that we see in our investigations
Types of Uncertainty you will see
• 1.) Absolute Uncertainty
• Used when evaluating accuracy of tools
• Used when data processing involves addition and subtraction only
• Used for error bars in a graph when graphing processed data
• 2.) Average Uncertainty
• Used to evaluate how close numbers in a data set are to the stated average
• Ex (-1, 0 and 1 ) vs. (-1000, 0, and 1000)
• Used as error bars when graphing averages
• 3.) Percent Uncertainty
• Used when multiplication or division are used in data processing
Absolute Uncertainty
•
Finding Absolute Uncertainty of a tool (Raw Data)
• Option 1.) Use the “published value” for your device
• EX: Our balances have an absolute uncertainty of +/- .001 g
• Option 2.) Use the rule of thumb of “half the smallest certain digit”
• If you use a mm ruler you can usually estimate if an item has a length that falls between 34 mm and 35 mm. You would call that 34.5 mm. “Half the smallest certain digit” refers to our ability to estimate with analog devices
• Digital Devices make that estimation for us so we use ± 1 of the smallest increment displayed
•
Propagated Absolute Uncertainty – used with +/- Processed Data
or as error bars on graphs
• Add together the Absolute uncertainties of each measurement in your answer
Average Uncertainty
• Equation = (|a-x|+|a-y|+|a-z|) / n
a= average
x,y,z = example data points n= number of trials
You will use this anytime you are taking an average of your data set that has less than 5 trials. This usually means you will see it in your Processed data, however there are time when it makes sense to take an average in your raw data section.
Standard Deviation
• When using a data set that has 5 or more trials in each manipulation, you will want to evaluate the average of those data with Standard
Percent Uncertainty
• Equation = ((absolute uncertainty)/Measurement) x 100 %
• Used when data processing involves any multiplication or division
• Never used for error bars on a graph
• Percent Uncertainty in Raw Data
• If you know your data processing will involved multiplication/division you may use % uncertainty in your raw data section
• 1. Find Abs. U of each measurement
• 2. Plug into formula
Graphing with Error Bars
• Each graph that you do should have error bars associated with each data point.
• You will use either Absolute Uncertainty or Average
Uncertainty to create these error bars.
Conclusion- Response to RQ
Goal – Discuss trends, compare to published context, and evaluate the strength of your data/findings.
Discussion of Results- This section will serve to respond to your
research question. You must support this response using data in your processed data section, by referencing specific data points in specific tables. You must also provide a molecular explanation for this
Conclusion- Comparison to Scientific Context
• Comparison to Scientific Context – Compare what you found, or
trends/patterns you saw to published research. (Published = peer reviewed aka real science) Talk about if your findings agree or
Conclusion- Evaluation
• Strengths - What about your design makes your data trustworthy or
valuable.
• Ex: Multiple trials, uncertainty evaluations, consistent methods, elegantly designed procedures
• Weaknesses - What about your DESIGN makes your data/findings
untrustworthy. When talking about user error point out where and how your
data was affected
• Further Experiments Knowing what you know now, what further
Formatting
• Follow APA format
• Use about size 12, please don’t go under 10
• Do not use first person unless you’re in personal engagement, use 3rd person present tense.
• Double Space regular text
• Single Space anything within a table
• Use a 1 inch margin
• Citations- must be included in background and conclusion • Can print double sided
• Label each table, graph and figure in the order in which they appear
