IB Data Analysis Practice 2
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IB Data Analysis Practice 2

In this activity, you will practice creating the most common graph used in IB Biology, the scatter plot.  Additionally, you will conduct a polynomial correlation test and use standard deviation to depict the degree of uncertainty in the data.  It may be helpful before, during, or after completion of this activity to examine the explanation of IB Lab Standards that outlines the specific requirements for each component of the Analysis Standard.  They can be found here.

Part A: Creating a Table

1. Create data tables (one raw and one summarized) using the randomly organized data below. Each value represents a different trial where each temperature has six trials.
2. Tables should be arranged so that rows/columns are labeled.  All rows/columns must have units and uncertainties.
3. All tables must have a title that specifically indicates what is being presented.
4. Tables are generally arranged in this manner to make calculations easier in future steps.
5. Provide sample calculations (only one example per calculation) for any calculations used.

Part B: Calculating Mean and Standard Deviation.

Excel makes it extremely easy to calculate mean and standard deviation very quickly for large datasets.  Calculate both of these in Excel (don’t use a calculator) by watching the following video:

Calculating mean, median, mode, and standard deviation in Excel.

Part C: Creating an X-Y Scatter Plot Graph.

An X-Y Scatter Plot graph allows two numerical data groups to be compared with one another.  For example, how does the mass of birds compare with their beak length?  In this example, and for nearly every data collection opportunity, there will be multiple trials for each variable.  In this case, there are five different beak lengths identified and five bird mass samples for each bird beak length.   Using the calculated mean, create an X-Y scatter plot graph for the sample data using the following video:

How to create an X-Y scatter plot graph in Excel

Hot to create a X-Y scatter plot graph in Google Sheets

Part D: Creating Error Bars on an X-Y Scatter Plot Graph.

Anytime data is collected for a number of samples of the same category, there will almost always be variation in said data.  By using standard deviation, one can calculate standard of the mean as a way to indicate the reliability of measurements as an indicator of the true mean for the entire population.  Using this value and a confidence interval of 95% can be used to show, with 95% confidence, what values would the true mean would be expected to fall within.  Using the calculated standard deviation, standard error of the mean and 95% confidence interval add error bars to your graph after watching the following videos:

How to calculate Standard Error of the Mean & 95% Confidence Interval

Mr. Murray explains how to create Google Sheets Error Bars

• Biology always uses the 95%CI for error bars, but the process is the same

How to create Excel Error Bars using 95% Confidence Interval

Part E: Creating a Polynomial Regression Line for a Correlation Test

A correlation test can indicate the correlation or degree of relatedness between two data sets.  As discussed in class, this is merely a suggestion and does not necessarily prove two data sets are correlated.  However, the test can be useful and will be used throughout IB Biology.  For example, a correlation test could indicate the relatedness between bird beak length and mass.

A correlation test can be accomplished in Excel by adding a line of linear regression or a polynomial regression line to examine a peak value; Using the same graph and data, add a polynomial regression line and R2 value to indicate the correlation between bird beak length and mass in which the R2 value is the correlation value by watching the following video:

How to create Polynomial Regression Line for a Correlation Test

Part F: Turn-In

Organizing graphs and spreadsheets for printing or screenshots from Excel can sometimes be just as challenging as creating them.  Take a screenshot of the data table(s) and graph by clicking the keys “shift+command+4” (on a Mac) at the same time, highlight the desired portion of the screen and release the mouse to take a screenshot;  alternatively copy and paste the data tables and graph or in Excel right-click on the graph to save as an image. Create a Google Document to upload the screenshots on (click on “insert” and “image”), add the new document to the assignment and turn in.

Printing & Organizing Data Tables & Graphs from Excel

Assessment: Analysis

 IB Mark Analysis Descriptor 5-6 The report includes sufficient relevant quantitative and qualitative raw data that could support a detailed and valid conclusion to the research question.Appropriate and sufficient data processing is carried out with the accuracy required to enable a conclusion to the research question to be drawn that is fully consistent with the experimental data.The report shows evidence of full and appropriate consideration of the impact of measurement uncertainty on the analysis.The processed data is correctly interpreted so that a completely valid and detailed conclusion to the research question can be deduced. 3-4 The report includes relevant but incomplete quantitative and qualitative raw data that could support a simple or partially valid conclusion to the research questionAppropriate and sufficient data processing is carried out that could lead to a broadly valid conclusion but there are significant inaccuracies and inconsistencies in the processingThe report shows evidence of some consideration of the impact of measurement uncertainty on the analysisThe processed data is interpreted so that a broadly valid but incomplete or limited conclusion to the research question can be deduced 1-2 The report includes insufficient relevant raw data to support a valid conclusion to the research questionSome basic data processing is carried out but is either too inaccurate or too insufficient to lead to a valid conclusionThe report shows evidence of little consideration of the impact of measurement uncertainty on the analysisThe processed data is incorrectly or insufficiently interpreted so that the conclusion is invalid or very incomplete 0 The student’s report does not reach a standard described by the descriptors above.

A full explanation of the lab standard rubric can be found here