Order 1223333: To what extent have human activities impacted the water quality in 5 waterways?
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HowtowriteagoodESSlabreport20163.docx
ESS LAB REPORT GUIDE
IDENTIFYING THE CONTEXT AND THE RESEARCH QUESTION
A good format is “How does [the independent variable] affects [the dependent variable] in [the context of your experiment]?”
e.g. How does hair length affects the insulating power of fur in polar bears (Ursus maritimus)?
e.g. How does salinity affect the germination of wheat seeds?
You need to state a focused research question. To do this you should:
a) Briefly state what you are trying to find out.
b) Include both the independent and dependent variables. Format the RQ according to the box on the right.
c) State the context of your investigation. You need to discuss a local or global environmental context/issue and explain the links between your research question and the issue.
PLANNING
a) The method needs to be repeatable, so write it as though someone else could do your lab with your instructions.
b) You must justify your choice of method, which is often a sampling method.
c) You must consider the quantity of data needed to be sufficient (enough) to answer the research question.
d) You must plan to make your readings as precise and accurate as possible through the use of appropriate equipment.
Variables are factors that may affect the outcome of your experiment. They are measurable factors, not pieces of equipment. Do not use the word “Amount”. It is not specific enough – terms like mass or volume are better.
Independent variable: This is the variable that you manipulate – you choose the values to investigate.
Dependent variable: This is the variable that changes in response to changes in the independent variable. It is what you are measuring or trying to find out.
Controlled variables: These are other factors that may also affect the dependent variable. They need to be kept constant in order to ensure a fair test.
PLANNING: Identify the variables
Example
Controlled variable
Method to control the variable
Temperature at which reaction occurs
The test tubes in which the reaction occurs will be placed in a water bath set to 40C for the duration of the reaction.
Duration (time) of the reaction
The reaction will be allowed to proceed for 300 seconds. This will be timed using a stopwatch (0.1seconds).
a) State the independent variable.
b) State the range or extent of the independent variable that will be tested e.g. 1g, 5g, 10g etc
c) State the dependent variable.
d) State how the dependent variable will be measured (if it can’t be measured directly). E.g. You may measure time and volume then calculate rate.
e) List several controlled variables. Choose the ones which might have a real effect on the dependent variable, not less important ones that may not.
You should explain in the method you will use to control each of the (controlled) variables.
f) Give brief (but specific) explanations of how you will control (keep at a constant value) each variable.
g) If a variable cannot be controlled, state this. Then describe how you will try to minimize any change and/or how you will monitor the variable.
PLANNING List the equipment (apparatus and materials) needed
Choose appropriate equipment.
Make sure that your equipment list includes all of the following:
a) All of the equipment and materials needed for the experiment (after writing you method read through it and check of the items used as you go on your equipment list)
b) Numbers of items (e.g. 2 scalpels)
c) Volumes and concentrations of any solutions needed (e.g. 300ml of 0.5M hydrochloric acid)
d) Precision (and range if appropriate) of all measuring instruments.
e) Sizes of beakers or other items (e.g. 250ml beaker, 10cm length of dialysis tubing)
f) If you can, put the uncertainty of the accuracy of each piece of equipment, (e.g. 50ml measuring cyclinder, ±0.5ml.)
PLANNING Write a method
You need to collect sufficient relevant data. This means there should be enough data over a wide enough range to adequately answer the research question.
a) What values of the independent variable should you test?
i. How many values should you test? Decide how many values will be needed to show any trend or pattern. Always plan for an ideal situation – worry about time constraints later.
Number of Values
If you are looking for a correlation, usually (not always) 5 different values are needed but the more the better. Sometimes less are appropriate depending on context.
ii. What is an appropriate range of values?
Range of Values
You may need to do some research to help you decide.
e.g. if testing productivity in aquatic plants, then a range which represents the natural extremes normally experienced by the plants would be sensible, e.g. 10, 13, 16, 19, 22 degrees etc
b) How will you measure your independent and dependent variables?
a. Can you measure it directly (raw data) or do you need measure other values and use them to calculate values (processed data) for your independent variable?
b. What measuring instruments will be best to use? Do you know how to use them?
c. What level of precision is required in your measurements?
d. What units will you use to record your measurements?
c) How may trials or replicates need to be carried out?
Number of Trials
Environmental systems, because of their complexity and normal variability, usually require replicate (repeated) observations and multiple samples of material. A good rule is to aim for 5, but sometimes this is not necessary. For example, if you measure turbidity or water temperature and get the same reading twice, it is unlikely to be necessary to do more readings.
A clear, easy to follow method is necessary for good communication.
Imagine that someone (who has not done the experiment before) should be able to follow your procedure and get similar results.
The following features contribute to writing a good method.
a) The method can be written as instructions like a recipe
b) Do not begin with “Gather all of the materials” … it is kind of a given that you will do this!!
c) Use numbered steps (rather than paragraphs).
d) Use a diagram if possible to show how to set up any equipment. Then you can say “Set up the equipment as shown in the diagram”. This would save you writing a lot of words.
e) Specify what will be measured (and the units to be used)
f) Include details of how you will measure values
RESULTS, ANALYSIS AND CONCLUSION
RAW DATA refers to the values from the measuring instruments exactly as they were shown. Once you do any addition, subtraction, multiplication or division then it becomes PROCESSED DATA.
1. Record ALL your raw data
Quantitative data – numerical values obtained from the measuring instruments (e.g. temperature, mass etc) or by other means e.g. counting
Qualitative data – non-numerical observations. Other observations made during your experiment that may have a bearing on the conclusion or help to explain patterns and trends (or the lack of!). Examples include changes in colour, texture, size etc. Any other observed sources of error should also be recorded.
Even if the data is unexpected or contains mistakes, you must show it.
Raw data should include quantitative (always!) and qualitative (almost always) data.
Raw data should be displayed in a table (qualitative data may require some other format, but a table is till usually best).
a) Formatting your table
a. When possible, the independent variable should come first in your columns followed by the dependent variable.
b. Show lines around all rows and columns
c. Make it clear. A good table should be able to be understood out of context (i.e. you can understand it without the rest of the lab report)
b) Title
a. Title should describe the data contained in the table. It should include the key variables as well as any specific conditions of the experiment
b. If there is more than one table, number them.
EXAMPLE
Table 1: The relationship between temperature and water uptake in a leafy shoot of a geranium (Geranium carolinianum)
c) Headers and units
a. Columns should be clearly annotated with a header, and units (in the heading not with the data)
b. Headings should indicate what the data is in the column below
c. Headings are likely to be the name of a variable (independent or dependent)
d) Precision of data
There is no variation in the precision of raw data; the same number of decimal places (significant figures) should be used.
e) Anomalous results
Any results that are particularly different from the others need to be identified and excluded from any processing (but shown in the raw data).
Here are some examples of decent tables. Yours might be very different.
Here is a table of qualitative data:
2. Process your data
Data processing involves combining and manipulating raw data to determine the value of a physical quantity (adding, subtracting, squaring, dividing), and taking the average of several measurements and transforming the data into a form suitable for the graphical representation.
a) Look at Your Research Question
ALWAYS CONSIDER YOUR RQ.
The purpose of processing data is to show patterns in the data that help you draw a conclusion that answers your research question
b) Choose Your Processing Technique, some options are
Change in quantities
· Change in quantities (initial final)
This is a very basic processing technique and should be used in combination with other methods.
Percentage change in quantities
· Percentage change in quantities.
This also allows you to compare quantities that have different initial and final quantities
· Rate
Rate is a measure of how quickly a variable changes
· Mean (average)
When you have multiple trials in an experiment, calculate the mean.
3. Present your processed data
You are expected to decide upon a suitable presentation format without teacher assistance.
a) Present data so that stages of calculation can be followed
Show one fully worked sample calculation for each type used.
If Excel or a graphing calculator was used to generate values simply state this.
b) Decimal places
Your processed data should not have more decimal places (or significant figures) than the raw data you collected
c) Presentation formats
A few general options are listed below; but you are not limited to these options
· Spreadsheets and tables showing data calculations such as mean, percentage change etc.
· Line graphs and scatter-plots showing continuous data points (e.g. time, concentration, age, heart rate, height etc.) with line of best fit
· Bar graphs showing discrete data (categories) e.g. species, phenotype, sex, ethnicity
· Pie charts showing percentages out of 100%
· Biological diagrams to illustrate changes in appearance (should be used in combination with other methods)
· Photographs
Diagrams and Tables
There should be clear, unambiguous headings for diagrams and tables or graphs similar to the headings used for tables in your data collection.
Diagrams will be labelled as figures. Figures should be numbered for reference and be placed below the figure it references.
Graphs
A graph is a visual representation of the data that allows you to answer the research question. It should look like this;
Dependent variable/ units
Independent variable/ units
Graphs must have the following:
· Title. The same expectations apply as for table (see section on Recording Raw Data).
· Appropriate scales; if you are measuring temperatures between 30 and 40 degrees, your graph should not begin and end at 0 and 100 respectively. Your units must be appropriate as well. If you are measuring in mm, you shouldn’t have meters marked on your graph.
· Labeled axes with units; axes should be labeled similarly to your table headings.
· Accurately plotted data points should be clearly shown, visible, and not too big as to obscure data
· A suitable best-fit line, trend line or curve is drawn (for a line graph or scatter plot) DO NOT CONNECT THE DOTS !
Do not let the software choose the formatting or the best fit line. The best fit line should be chosen by you to reflect the trend that you judge to be appropriate.
You may choose to add standard deviation or range of data error bars and R2. The error bars should be labelled below the graph e.g. “Error bars show ±1 STDEV.” If you include error bars or R2, you must include an analysis of what they tell you.
Here are some decent graphs. Yours may be very different.
4. Write a conclusion
· Clearly state any patterns or trends you see in the data.
· Be very careful to answer your research question.
· Do not miss smaller patterns. For example, even though the trend might be “downwards” there may be a plateau at the start, or the end.
· Use your results to justify your conclusion, state actual figures.
· Describe what your results show in the context of your topic of investigation
· Compare these to literature, scientific understanding or models or class discussion. If there are differences, identify them and suggest possible reasons
· Identify any anomalous results and justify their exclusion from processing
· All sources used to write your lab report should be fully referenced by using MLA formatting.
Don’t lie! State what you see, not what you wished to see.
DISCUSSION AND EVALUATION
1. Evaluate your conclusion in context
Does your conclusion fit in with the context? Does it support, or not support the ideas of the context. Don’t just make simple statements. consider ways in your conclusion does or does not fit in with the context.
“Evaluate” means make judgments about the extent to which your data fits in with the ideas you have learned. How valid are your own conclusions? How well have you answered the research question?
Mention R2 or error bars to justify the validity of your conclusions.
2. Discuss strengths and weaknesses in your investigation
This is where you comment on the design, method of the investigation, and the quality of the data. A good format for the Evaluation is shown to the right.
Good format for Evaluation
Strength/Weakness
Significance
Improvement
a) List specific strengths in the design and carrying out of the procedure.
b) List specific weaknesses in the design and carrying of out the procedure.
For both of the above consider….
i. procedures,
ii. limitations and use of equipment,
iii. management of time, investigation timing
iv. data quality (sufficiency, accuracy and precision) and relevance of data.
v. Unavoidable errors, such as variability of materials
c) For each strength or weakness discuss its significance i.e. it’s effect on your results e.g. values too high/low, data values less reliable (large uncertainty/error/S.D. would indicate this), measurements less accurate or precise, trend/pattern incorrect or unclear etc
Acceptable Example:
“Because the simple calorimeter we used was made from a tin can, some heat was lost to the surroundings—metals conduct heat well. Therefore, the value we obtained for the heat gained by the water in the calorimeter was lower than it should have been. The heat lost from the tin can would not have been a lot in the time taken for the experiment so this probably did not have a significant impact on the results”
Unacceptable Examples:
"The test tubes weren’t clean.” careless or poor performance does not make for a valid weakness
“Human error.” a specific description of the type of human error would be required
Describe improvements for each identified weakness
For each improvement ensure that:
a) Suggestions are specific (numerical if possible). “Next time we should work more carefully” is not acceptable.
b) Suggestions are realistic – they can be achieved within the constraints of the timetable, school setting and budget.
c) Improvements are not overly simplistic or superficial – you need to demonstrate that you are a student at a Diploma level!
Accuracy = how close a measurement is to the correct value
Precision = exactness of a measurement as represented by the number of decimal places to which it is expressed
Reliability = consistency in measurements (i.e. if measurements taken over consecutive trials are all very similar then there is consistency and they are said t be reliable). This can be shown by the standard deviation.
APPLICATIONS
Based on what you have learnt in your experiment, either
· Apply this knowledge to the environmental context/issue under investigation, or
· Suggest a solution to the environmental issue.
You should justify your application or solution by directly linking your work with the context/issue, and providing evidence from your findings to support your application or solution.
Evaluate your application or solution. Again, this means judging your own ideas – give pros and cons of your idea.
COMMUNICATION
To score well on communication:
· Answer all sections in order.
· Use headings and titles throughout.
· Use suitable language (no slang, don’t “grab” your equipment.)
· Use the specific terms you have used in the course.
· Use a sensible font (12pt) and avoid the use of colour in tables (only use it if necessary in graphs)
· Avoid cramping too much onto a page.
· Follow all conventions regarding tables, graphs and other figures.
· Cite any and all sources.
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ESS Lab Report Guide
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