Outline Biology Ia 5g5eb

Internal Assessment Lab Format The following titles and subtitles should be used for your lab report and given in this order within your lab report. Everything should be in Times New Roman, 12 point font, double-spaced lines

TITLE must be unique to your experiment Background This is the place to summarize what you have verified about the topic using research. Use reputable online sources, but you can probably start with your text book. You should have a minimum of two sources cited at the end of your report (No Wikipedia). You may repeat some of this information in your conclusion when comparing your results to literature values and when explaining your results. When you proofread this section, make a list (actual or mental) of the scientific facts used. If there are none, you need to rewrite. (1/2 page maximum)

Design Problem – must be focused and not ambiguous in any way. Restating the question posed to you is not sufficient. Your question should be more focused than the question I posed to you.

Hypothesis – state first & then give a logical rationale – your conclusion should address the hypothesis you are giving here. Information in your background section should be repeated and used to your hypothesis. Do not assume that the reader can tell which parts of your background research your hypothesis. State the science behind your hypothesis explicitly.

Variables – chart or list identifying Independent, Dependent, & Controlled Variables. Include in this chart how dependent variables will be measured, and how & why controlled variables will be controlled. For example, if you are assuming that temperature will be controlled by the air handing system for the building, state that. Dependent variables should be measured quantities, not calculated quantities. If you are planning on calculating density, mass or volume is the Dependent variable, not density. A rate of increase (slope) is also a derived variable.

Materials – make a table listing precisely what materials you are using and what you will use it for. "250 mL beaker" not "beaker", "electronic balance" not "balance", "100 mL graduated cylinder" not "graduated cylinder". For any chemicals used, identify the compounds precisely including concentrations where appropriate.

Experimental Setup – annotated photograph showing how variables were instituted, especially the controlled variables. This is not just a variety of equipment sitting next to each other. Can be a drawing if necessary.

Procedure – write a numbered list of steps that can stand alone and be followed by any classmate. Be sure to include details of data collection. Saying you will "collect data" is not sufficient, under any circumstances. If you're measuring length, say you will measure the length with a ruler, not just measure the results. Include multiple trials in your procedure!!! Five is generally a good goal. Even if you are sure you will run out of time to do 5 trials, put at least 5 trials in your procedure (10 minimum if you use a T-test)!! Don’t exaggerate the number of trials you plan on doing either. If the procedure is simple enough to do 100 trials, say you will do 100 trials, but don’t say that unless you know there is enough time. State the method of data analysis as the last step.

Safety - Include any appropriate safety precautions, including use of goggles and aprons (if appropriate).

Data Collection and Processing Raw Data Table – make sure this is raw data only. Data table design & clarity is important. A title should be given (Raw Data Table is not a data table title, it is a lab report section title) Make sure that all columns, etc. are properly headed & units as well as symbols are given. Forgetting one unit or misidentifying one unit is enough to drop your score in this section. Do not “split” a data table (putting part of a table on one page and finishing it on another). If you absolutely have to split a table (due to quantity of data), make sure that you re-do the title and all column headings. Uncertainties are mandatory and can be given within column headings for equipment precision and as footnotes beneath data tables for other types of uncertainties. Omitting the uncertainty in any quantitative data will drop your score. Be sure that the reported significant figures in your tables “match” the uncertainties of the instruments.

Raw Data Graph – this will typically be a bar or line graph showing values for each individual. there are no error bars on a raw data graph. Think about title, axis labels, units, scale, etc.

Observations - You must include qualitative data in addition to quantitative data. There is always some relevant qualitative observation that can be made, even if it is as simple as observing the expected color change. In Biology, it might be the observation that the test tube of the enzyme catalyzed reaction became hot, or the plants appeared wilted.

Data Processing Overview – this is a short paragraph section that gives an overview of how and why you decided to process and present the data in the form that shows up later in this section. This should show that you understand why you chose to analyze this way!

Calculations – neatly lay-out and explain one example only of any type of manipulation that was done to the raw data to help make it more useful for interpretation. You should use formulas and units when appropriate. Label your calculations carefully so the reader knows what you are calculating. If you decide to type your report and hand write calculations, please put them in the correct place in your report. This section is

REQUIRED if your experiment doesn’t lend itself to calculations you need to write a new procedure. The minimum that you need to have is mean, standard deviation and your particular statistical test.

Presentation – this is typically 2 data tables (one for descriptive statistics like means, standard deviations, etc.; the other for statistical test (T-test or linear regression results) and 1 graph (should be a bar graph with error bars (standard deviation) for a T-test and a scatterplot with trendline for a linear regression). Again, the design & clarity of data table(s) is important and the quality of graphs is also very important. Give careful consideration to the choice of graph style(s) that you choose to do. that demonstrating errors and uncertainties in your data is also mandatory for the processed data. Be sure that the significant figures reported in your calculated data match the calculated uncertainties of your calculated data. Make sure that you follow good standard rules for doing graphs (valid title, axis’ labeled including units, etc.) Please put graphs in the correct place in your report. They should be BEFORE the conclusion and evaluation!

Conclusion & Evaluation Conclusion - this is a paragraph section in which you get a chance to discuss the results of your experiment. Start by addressing whether your data seems to or refute your hypothesis. This should be discussed and not just stated. Specifically refer to your graphs and statistics to give to this discussion. Avoid the use of the word “proof” or “proves” within your conclusion, as your data will not prove anything. Include comparisons to any literature values and important theories, another 2 citations minimum. (1/2 page maximum)

Limitations of Experimental Design – this paragraph section discusses how well your experimental design helped answer your experimental question. What worked well (and why) and what did not work well (and why). This is also a section in which outlier points could be discussed (if there were any outlier points) as well as possible reasons for those outlier points. Your error bars or standard deviations must be discussed. This is NOT a place to suggest a new experiment. Restrict your discussion to the experiment you did. Random errors (population is variable) and systematic errors (problems with your actual measurements) must both be explicitly addressed. (1/2 page maximum)

Suggestions for Improvement - in reference to the limitations given in the previous subsection, what realistic and useful improvements could be made if you were to do this investigation again? More trials only reduces random error. If you do not have any fluctuation between trials this isn’t really an improvement. More time gets you no points. A “better” stopwatch, ruler, etc. is too vague, and probably unrealistic. Use of calipers instead of a ruler, use of a photogate instead of a stopwatch are real improvements. This is not a place to suggest a new experiment with a different independent and dependent variable. Restrict your improvements to the experiment you performed!! Suggesting a different way of measuring or controlling the variables is encouraged, as long as it is a real improvement. Written reports are not an appropriate place to vent. (1/2 page maximum)