GENERAL ISSUES
All lab reports used for Internal Assessment (IA) must be printed out on A4 paper with at least a
20mm margin on the left of the page. It is better to have 20 mm margins both left and right as this allows space for comments. Stick to a basic font (Arial, Calibri, Times New Roman) that is large enough to read (10 or 12pt).
Try not to write in the first person. This means that you should try not to write using “I”, “We”,
“Us” etc. Use the 3 that…..”. rd person and in passive form. For example, don‟t write “I think it is going to jump…..”, use something like “It is believed that….”, “It was observed that….”, “It was found
You can also cite outside sources as a way of avoiding the first person. “Based on the findings of
Collar & Webb (2008), it is predicted that…….”
Figures (pictures, diagrams and photographs), Tables & Graphs must all have a specific number and have a clearly understandable and focused descriptive title. For ex ample, don‟t write “Graph showing data from Table on next page”. Use something like “Graph 3: Line graph showing the relationship between the length of bean sprouts and the application of varying concentrations of phosphorous over 10 days ”. More details are given in the section dealing with Data Collection &
Processing.
The first 2 pages of the lab report should be: o The rubric/s being assessed. o The instruction sheet for the lab.

For a planning lab you are required to have the following sections:
TITLE
The title must reflect the research question and should be engaging
INTRODUCTION
An introduction
An introduction sets the scene for the whole of the report. It only needs to be 2-3 paragraphs long and should be about the topic being investigated. For example, if you are investigating the influence of
Nitrogen on plant growth, you would write a brief account of what is known about the effects of this nutrient on the growth of plants. In-text referencing is usually required as this section is not only your work.
A clearly stated research question or problem
The research question needs to be specific and focused. You need to indicate the variable chosen for the investigation. Think about this very carefully. A poor question would be “How does phosphorous affect plant growth”. A good research question would be “How does changing the concentration of available phosphorous in irrigation water affect the growth of the marine grass Sporobolus virginicus ?”. If you want to see how professional scientists write research questions just look at the titles of articles in journals (on the web) such as Science, Nature, PLOS and Ecology & Society.
An hypothesis (not strictly required but this will help focus your work)
Not all investigations will have an hypothesis – but – most will, and they are a very good way to focus your thoughts and ideas. o An hypothesis should be clearly stated as a prediction – “Based on the work of Collar & Webb
(2002), it is predicted (in this investigation) that……..”. o It should be quantitative if at all possible. o If there is a clear mathematical relationship between the Independent Variable (IV) and the
Dependent Variable (DV) this needs to be stated in your hypothesis.
A scientific justification of your hypothesis
You must show that you have done some research on the subject through the justification of your hypothesis. You will need to provide reasons for why you think your hypothesis will be the outcome – this is not a personal view, it is a view based on sound scientific judgments based on your research. You should cite sources listed in your bibliography. The justification (scientific explanation) may require discussion of equations, general principles, laws and published examples.
A clearly laid out section on variables
This is where you have the greatest potential to lose marks in the Planning Criterion. Two of the 3 aspects are focused on variables. Make sure you put in the time to get it right.
This is what the IB says about variables:
“Variables are things we measure, control or manipulate in an investigation. Independent variables are those that are manipulated, whereas dependent variables are measured or registered. The variable one decides to manipulate is independent, the variable that depends on the manipulation is dependent. Thus, in a calorimetry investigation, where a candidate measures the temperature every 30 seconds, time is the independent variable, and temperature is the dependent variable. Similarly, in a rate investigation, where the candidate measures the time taken to collect certain volumes of gas, volume is independent, and time is dependent.”
This section should include information on:

o Independent Variable (IV) – name it, include units of measure, describe it. Include a statement of the range of the data values that will be tested. If necessary explain the IV and what is actually measured – e.g. you may be measuring productivity in g/m 2
/day and converting that into tonnes/year in your graphs o Dependent Variable (DV) – name it, include units of measure, describe it. If there is a mathematical relationship easily understood in an equation give this here. Explain how you derive the DV if it is not directly measured – e.g. Sustainable Yield would be derived from data on the total population and birth rates (recruitment). o Controlled or Fixed Variables – List (name) the variables that you will actually control. Provide a brief description of each variable and the parameters of the control (how you will control the variable) – e.g. „Light will be controlled using a fixed intensity of light (100W) and a daily rhythm of 12 hours of light and 12 hours of dark‟. In your description include information on why you need to control the variable. Be specific and focused.
Do not list those things you cannot control or fix (e.g. atmospheric conditions outside when you are in the field) but you should be able to account for any influence of these uncontrolled variables on your data in the discussion and evaluation sections of a lab report.
PROCEDURE
Materials
Provide a list of all the equipment used in the investigation. This should include the quantities required, the sizes of the different beakers etc, the chemicals required (named) and quantities and types of materials (e.g. distilled water, tap water). Be specific but don‟t be pedantic.
Diagram or photograph of your experimental set-up
You can include a diagram or a photograph of the experimental set up if you find it necessary. Please remember that if you use a picture it is referred to as Figure # (with a descriptive title) and you must discuss it in the text somewhere. Otherwise it is just a picture in your lab report.
Procedure
This is a numbered list of clear, exact steps to follow – described in a brief and focused manner. Nobody likes reading this part, so be clear and brief. The steps in the experiment should either be self-evident or briefly explained. You should aim to describe a method that would enable someone to carry out the experiment.
You need to explain the different variables (to a certain degree redundant if you have done it well in the variables section but you will find this section will be very easy then). o Explain how to change or manipulate the IV (and measure giving units) o Explain how to measure the IV (units and errors) o Explain how to control the CV/FV. The IB states that “The method should include explicit reference to how the control of variables is achieved”. For example, if you are weighing samples you need to state that you collected the data using the same balance every time. Or you controlled temperatures by using a waterbath set at 24°C.
Check that your described method allows you to record all the relevant data that would be required to determine whatever quantitative value is being investigated. You must include instructions on the range of values for the IV (treatments) (these should cover a wide range rather than be too close together), the number of repeat measurements for each value (number of trials) and that you are clear about any mathematical equations or formulae that need to be used in the processing of the data.
A Raw Data Table to show how you would collect your data
REFERENCES/BIBLIOGRAPHY
A full set of references in the correct format (MLA is preferred). These must be consistent and done in alphabetical order. In text referencing must follow a clear and unequivocal standard.

CHECKLIST FOR PLANNING LABS
Aspect 1: Defining The Problem And Selecting Variables
□ I have identified a focused problem or a specific research question. I have done this by stating a clear aim, a clear hypothesis, and clearly defining the variables.
□ I have identified and stated the independent variable and the dependent variable, and I have listed the controlled variables
Aspect 2: Controlling Variables
□ I describe a method for the effective control of the variables. In particular, I describe how the independent variable is manipulated and how the controlled variables are maintained at constant values
□ I list all the apparatus and materials used, including the volumes of tubes and cylinders, the concentrations of solutions, the model and manufacturer of any complex apparatus, etc.
□ I state the level of precision of the values for the independent variable
□ Any standard methods that I use are fully referenced in a footnote or in the references
Aspect 3: Developing A Method For The Collection Of Data
□ I describe a method that allows for the collection of sufficient relevant data
□ The data gathered enables the aim, the research question or the hypotheses to be adequately addressed
□ The data gathered enables an evaluation of the reliability of the data
□ The sample size should be adequate to allow a reasonable statistical analysis of the data (for calculating the standard deviation, at least five items per treatment)
□ An adequately broad data range is considered
□ An adequate number of data values within this range are considered

Student Name:
Investigation Title:
Date:
States a focused problem/research question and identifies the relevant variables.
States a problem/research question that is incomplete or identifies only some relevant variables.
Does not state a problem/research question and does not identify any relevant variables.
Designs a method for the control of variables.
Designs a method that makes some attempt to control the variables.
Designs a method that does not allow for the con\trol of the variables.
Describes a method that allows for the collection of sufficient relevant data.
Describes a method that does not allow for the collection of sufficient relevant data.
Describes a method that does not allow for the collection of any relevant data.

This is the criterion that causes the fewest problems for students and if you follow the guidelines of the rubric closely you can score well. This is the section of a scientific publication that would be called the
RESULTS. There are very specific expectations in this type of lab – most of which are logical and easy to understand.
The DCP (Results) section is arguably the most important part of any research report as this is where you bring together and report your findings. When done properly, this section will present your results clearly and in a way that shows that you have organised your data and carefully considered the proper analysis.
If you are doing a DCP lab without a planning section you will need to include the following sections that would normally occur in a Planning lab in more detail.
TITLE – same as Planning lab
INTRODUCTION o Introduction – same as Planning lab (be brief) o Research question – usually included but should be brief and must be different from that provided by your teacher. o Hypothesis – clearly stated with a scientific justification. Be brief, not as detailed as for a
Planning Lab o Variables – this section should be clearly laid out – show you understand the variables.
Not as much detail as a Planning Lab – be concise.
PROCEDURE – if the procedure is provided, make a brief reference to it and explain any modifications. No detail required. No data table required here.
For DCP labs you are not directly assessed on any of the preceding information but it is important to have a brief and focused introductory section because it allows the examiner to understand the context of the data AND that you know what it is that you are doing!
DCP labs comprise the following:
DATA TABLES
There are 2 types of tables –
Raw Data Tables which comprise the data collected in the field or lab, and
Processed or Final Data Tables which are a synthesis of the data in the Raw Table. Final data tables summarise raw data, show any data transformations performed and the results of any statistical tests.
You must include both.
All tables must have a number and a title. E.g. Table 5: ANOVA analysis of the association between the winter catch rate for mudfish Gala tribolius and four habitat parameters. In science there is a convention that the title goes above the table.
In investigation where there is pooled/group data, you need to identify your own data clearly.
All tables must be numbered in sequence so that you can refer to them easily in the text.
All columns in tables must have a heading and units.
IV is in the first column and recorded data in subsequent columns across the rows
Errors (and uncertainties) where applicable should be included in a column heading or a separate column
Tables must show the quantitative data collected. All quantitative results must be recorded to the appropriate level of accuracy and must be recorded consistently (sig.fig and dec.places).
MUST have the qualitative observations included either in a specific column or as notes appended to the relevant table.

MUST include Fixed Variable data, usually in the Raw Data table but can be in a table of fixed values.
Within a column all the data must be shown with the same number of decimal places or significant figures.
Decimal places in the processed data must match the raw data. You cannot have processed data to 3 decimal places when you collected the raw data rounded to one unit!
Where you included statistical data you should indicate those statistical values that are significant and those that are not (and at what level e.g. P<0.5).
Tables must be neat, logical and organised.
CALCULATIONS
The demands of the ESS syllabus on the student with regard to statistical analysis of data are minimal.
Students are expected to be able to go beyond simple arithmetic calculations such as means and aggregated totals. You should however, know how to use or interpret simple descriptive statistics such as the mean, median, mode, range, frequency, percentages, ratios, approximations and reciprocals.
You are required to use standard notation, e.g. 3.6 x 10
4
.
You should collect data (or plan to) for at least 3 trials per treatment for any investigation. In ecological data it is better to have at least 5 trials.
You should be able to apply basic statistics such as: o Standard Deviation o Student‟s T-test
You need to show (and explain briefly) all calculations that are done on the raw data. You are only required to show one example of each calculation to show that you understand the calculation. This is important for the 2 statistical tests given above.
If you use an equation such as Simpson‟s Diversity Index you must show one example calculation for this formula.
Take care to use the correct number of significant figures and/or decimal places in all calculations.
GRAPHS
Graphs show trends or patterns in the data. Be sure to choose the correct type of graph and allocate enough page space for it in your lab report.
Every graph should have a number and a descriptive caption or title. Numbering must be sequential. In science that convention is that the caption goes below the graph.
Graphs should be printed large (at least half the page).
Remove the title provided by Excel and move the key to under the x-axis. This gives you more room on your graph.
Scale the graph axes appropriately. The axes should go beyond the points on the graph
Label all axes and include units
Keys should be provided either in the title, on the graph or as a note attached to the graph.
Decimal place values on the axes of the graph must be consistent with the data in the tables.
Trend lines should be given as a line of best fit (showing r values and intercept – but move these if they interfere with the data points or graph in any way).
Use error bars where appropriate. If error bars are too small to be seen, this should be explained in the graph title/caption with quantitative examples of the error bar size.
Present basic graphs first (i.e. show the fundamental data first) and then (if appropriate) present combined data projections, transformations and other complex graphs.
If using Excel use only graphic presentation options that print well in black and white. Do not use dark coloured backgrounds with coloured lines. Black and white graphs with distinct data points are best.

Show gridlines at an appropriate scale.
This section is, however, not just a series of tables, calculations and graphs. You need to highlight some of the key findings in short bridging paragraphs following tables and graphs.
You should keep your statements of important findings brief and you should only include results here – there is no discussion of the actual results. For example, “Mean summer water depths were only 3.6cm in areas with mudfish, compared to 39.5 cm at those sites with no mudfish”.
Refer directly to your tables and graphs in the text and you can highlight important differences between your results and any published results (you should not discuss these, merely highlight them). For example, “The results for the analysis of total dissolved solids (TDS), dissolved oxygen (dO) and secchi disc depths (cm) are given in Table 3.1. These were similar at all tests sites, in contrast to the findings of Miller (2001) who found that TDS was higher at sites with mudfish than at those sites without mudfish”.
Include units for all data references, e.g. “Total catch rates for all sites are similar (geometric mea n 0.70 fish per trap per night: Table 5.3)”.
These bridging statements and references to your tables and graphs make it easier for you to discuss your results later and for the reader to understand that you know what is going on in your investigation.
CHECKLIST FOR DATA COLLECTION AND PROCESSING
Aspect 1: Recording Raw Data
□ I have recorded my data independently
□ I have data which is quantitative (numerical)
□ I have chosen a suitable format in which to record the raw data
□ The variable that is measured or recorded is clearly stated (e.g. in the column heading in a table)
□ The units are given for every variable (e.g. in any column headings)
□ An indication is given of the uncertainty of measurements (e.g. in any column headings)
□ A complete and descriptive title is given to any table that is used
□ The same level of precision (number of decimal places) is used for all the items of a variable
Aspect 2: Processing Raw Data
□ I have decided on a suitable manner in which to process the raw data, so that I may fully test the hypotheses or fulfil the aim (this may involve mathematical processing, statistical analysis, or transforming the data into a suitable graphical representation)
□ All of the raw data has been processed to a suitable extent
□ The raw data has been processed correctly
□ Any raw data plotted onto a graph includes a line of best-fit where appropriate
Aspect 3: Presenting Processed Data
□ I have decided upon a suitable format in which to present the processed data.
□ There are clear, unambiguous headings for calculations, tables or graphs
□ Any graphs have appropriate scales, labelled axes with units and accurately plotted data points with a suitable best-fit line or curve
□ The data has been presented so that all the stages to the final result can be followed
□ Metric/SI units are included for the final results
□ The final results are shown expressed to the correct number of significant figures and/or decimal places
□ The uncertainties and errors associated with the raw data have been taken into account and this is shown in some manner (e.g. error bars may be used, as appropriate)

Date: Student Name:
Investigation Title:
Systematically records appropriate quantitative and/or qualitative data*, including units.
Processes primary and/or secondary data correctly.
Records appropriate quantitative and/or qualitative data but with some mistakes and/or omissions.
Processes primary and/or secondary data but with some mistakes and/or omissions.
Data is not collected or is recorded in an
No processing of data is carried out or major incomprehensible manner. mistakes are made in processing.
Presents processed data appropriately and effectively to assist analysis.
Presents processed data appropriately but lacks clarity or with some mistakes and/or omissions.
Presents processed data in an inappropriate or incomprehensible manner.
Marks: /2 /2 /2
Total: /6

This section is a real challenge – it is where you are required to show that you can apply your knowledge, interpret your findings and propose further work. In other words, you have to show that you know what you have been doing.
In this section of a report you are required to interpret your results in the context of the specific questions you set out to answer in the investigation. You should place your findings in the framework of any broader relevant issues (often with reference to findings or data from published sources). You must be prepared to discuss any unexpected or conflicting results. Once you have interpreted the data and given an account of your findings (discussion) you then develop a concluding statement that directly addresses your research question and hypothesis and how/why the results support or do not support your hypothesis. The evaluation section of the report is often difficult. You are required to critically evaluate any problems with your study design, unexpected and conflicting results, how and why these results may have come about and to propose realistic improvements or extensions to the investigational procedure.
The sequencing of the following sections follows the rubric – Discussion, Evaluation, Conclusion. If you think that it is more logical to do the report in a different sequence by all means do so. It is sometimes easier to do – Discussion, Conclusion, Evaluation.
DISCUSSION
This is the interpretation of your results. Support your statements with reference to Tables,
Graphs and data in the DCP results section. Some of the details that you should include are: o A discussion of the errors/anomalies in the data o Any random errors and how they affected your data o Any systematic errors and how they affected your data o A discussion of the precision and accuracy of the data. This should include an overall statement about the quality of the results and how confident you are in your results
The discussion explains the relevance of the results of the investigation.
Do not introduce new results in this section. You should have highlighted the relevant data in the
DCP section. You can, however, provide supporting or contrasting results from published studies but these must be cited using in-text referencing.
Your discussion needs to be clear and well reasoned. In other words, it should have a logical and progressional structure. For example, Graph 1/Table 1, progress to Graph 2/Table 2 etc – building up the information to support your conclusion.
You discussion needs to show a broad understanding of the context. You need to have done some research beyond your direct investigation. This may be as simple as stating how the results support what has been discussed in class/in your textbook.
You need to be sure to explain the implications of your results in a broad context. For example, if you are studying the effects of pH on plant growth, how do your findings fit in with what is known about acid rain.
EVALUATION
This section of the report causes considerable problems for students. Look to do it in a structured, focused way and it will be a lot easier. The purpose of this section is to identify any problems, weaknesses, limitations or errors in your experiment and then to make recommendations as to how to improve t he process the next time you do the experiment. It is a section where you are saying “watch out for this”, “fix that” and “this could be better”.
The evaluation should include a brief discussion of the weaknesses, impacts and improvements in the following areas:

The experimental design. The focus here is the variables – were they appropriate, could they be better controlled, were the units of measure and the errors appropriate to the experiment.
The equipment you used. What problems, errors, corrections, standardisations etc.
The method/procedure you designed. This is where most of the comment usually comes in and should include a careful evaluation of: o Good procedures, bad procedures and improvements o How to improve the control of variables o How to reduce random errors
Your use of time. Be brief and to the point – don‟t spend 3 paragraphs confessing to not doing the work and how you are going to be better next time! This is about how you could improve your use of available time by improving the methodological approach not your personal organisation.
It is suggested that you consider using a table, horizontally across the full page and discuss these four points under the following headings.
WEAKNESS/LIMITATION
Outline the actual problem that you have identified and how it came about. Be quantitative (use numbers/data) to illustrate the problem
IMPACT ON RESULTS
What did it mean in terms of the results that you have collected. If you need to point out the error/problem in a graph or table.
IMPROVEMENT
How are you going to fix the problem. Be realistic and specific. This does not include saying “buy better equipment‟,
“be more organised”. . If appropriate, state if the improvement is going to improve accuracy, precision, reduces random error etc.
.
CONCLUSION
Your discussion should be built up in such a way to support your conclusion that should, ideally, come at the end of your discussion. The concluding statement does not have to be long or particularly detailed but should address your research question and your hypothesis. Your discussion serves as the scientific explanation of your conclusion and so you do not need to repeat much here – it is a synopsis of your findings and how your findings fit in with your research questions and hypothesis.
In order to have a complete based on the rubric (Aspect 3) your conclusion should include:
Restating the research question and the predicted hypothesis
A statement of what the results mean, particularly the relationship between the IV and the DV
A statement of whether the results support the hypothesis or not.
A brief statement of why this relationship exits (support or not). You can bring in outside research to assist your interpretation.
Aspect 1: Discussion and Review
□ I have discussed my results in a logical sequence, from basic findings to more complex interpretation of results.
□ I have included references to graphs, tables, diagrams and literature values in my discussion
□ I have included a discussion of the broader context of the results based on external research
□ I have included a discussion the implications of my results based on published research and/or current understanding
□ I have structured the discussion to support my conclusions in a clear and focused manner
Aspect 2: Evaluating Procedures
□ I have commented on the design and method of the investigation
□ I have commented on the quality of the data

□ I have listed the weaknesses of the study
□ I have assessed the importance of each of these weaknesses
□ I have commented on the precision and accuracy of the measurements
□ In evaluating the procedure, I have specifically looked at the variables, the processes, the use of equipment and the management of time
□ My suggestions for improvements are based on the weaknesses and limitations identified.
□ As appropriate, I address modifications to the experimental technique and the data range
□ The modifications that I propose are realistic and clearly specified
Aspect 3: Conclusion
□ I state a conclusion which is based on a reasonable interpretation of the data
□ If any hypotheses are being tested, I have stated whether the data supports these hypotheses
□ I give a justification for my conclusion
□ As appropriate, I compare different graphs, or describe the trends shown in my graphs
□ If I am measuring an already known and accepted value, I have compared my value with that in a textbook, in order to assess the validity of the result.
□ I fully reference any literature that is quoted.

Student Name:
Investigation Title:
Date:
Marks:
Discussion is clear and well reasoned, showing a broad understanding of context and the implications of results.
Identifies weaknesses and limitations and suggests realistic improvements.
Discussion is adequate, showing some understanding of context and implications of results.
Identifies weaknesses and limitations but misses some obvious faults. Suggests only superficial improvements.
Discussion is inadequate, showing little understanding of context and implications of results.
The weaknesses and limitations are irrelevant or missing. Suggests unrealistic improvements.
/2 /2
States a reasonable conclusion, with a correct explanation, based on the data.
States a reasonable conclusion or gives a correct explanation, based on the data.
States an unreasonable conclusion or no conclusion at all.
/2
Total: /6