Excel 2007 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems
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This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you.
Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2007 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.
Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.
to your research findings. 3.3 Alternative Ways to Summarize the Result of a Hypothesis Test It is important for you to understand that in this book we are summarizing an hypothesis test in one of two ways: (1) We accept the null hypothesis, or (2) We reject the null hypothesis and accept the research hypothesis. We are consistent in the use of these words so that you can understand the concept underlying hypothesis testing. However, there are many other ways to summarize the result of an
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fitting the entire spreadsheet onto one page. In either case, your spreadsheet will not have a “professional look.” Print this file so that it fits onto one page, and write by hand the null hypothesis and the research hypothesis on your printout. The final spreadsheet appears in Figure 5.12. Now, let’s use the second formula for the two-group t-test which we use whenever either one group, or both groups, have a sample size less than 30. 92 5 Two-Group t-Test of the Difference of the Means for
Title Rotated title Enter this y-axis title in the Axis Title Box at the top of your screen: EGGS PRODUCED Next, hit the enter key to place this y-axis title along the y-axis Then, click on any white space inside the chart but outside this y-axis title to “deselect” the y-axis title (see Fig. 6.18) 6.3 Creating a Chart and Drawing the Regression Line onto the Chart 119 Fig. 6.18 Example of a Chart Title, an x-axis Title, and a y-axis Title Legend (at top of screen) None (to turn off the
8.2 163 How to Interpret the ANOVA Table Correctly Objective: To interpret the ANOVA table correctly ANOVA allows you to test for the differences between means when you have three or more groups of data. This ANOVA test is called the F-test statistic, and is typically identified with the letter: F. The formula for the F-test is this: F ¼ Mean Square between groups (MSb) divided by Mean Square within groups (MSw) F ¼ MSb =MSw (8.1) The derivation and explanation of this formula is beyond the