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
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:
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:
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:
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:
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. Create a Google Document to upload the screenshots on (click on “insert” and “image”), add the new document to the assignment and turn in.
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