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Reading “A Handbook for Biological Investigation.”. Yes….. I expect you to read it! Maybe more than once!. Use This While You Read. No tests No quizzes Performance only: You must know the information and use it – like a reference book!. - PowerPoint PPT Presentation
Slide 1
Reading A Handbook for Biological Investigation. Yes.. I expect you to read it!Maybe more than once!1No testsNo quizzesPerformance only: You must know the information and use it like a reference book!Use This While You Read
2What is Science?What are the limitations of science?What are the underlying assumptions of science?Re-read it now and then continue.
Ch 1 Read the chapter thinking about the following ideas.
3Science is a process by which observations lead to hypothesis. (inductive logic step)Hypotheses are then tested through deductive logic (cause and effect)Rejected hypotheses make way for more research.Accepted hypotheses support, but DO NOT prove, ideas about how the world works.Science always leads to new questions, which must be tested!
What is science?4Science can only study natural phenomena.
Science cannot make moral judgments
What are the limitations of Science?
5All phenomena are natural The natural world works via cause and effect relationshipsThe study of small populations allows us to generalize about larger population behavior. (this is actually one of the most controversial or the ideas.)What are the underlying assumptions of science?6Focuses on the natural worldAims to explain the natural worldUses testable ideasRelies on evidenceInvolves the scientific communityLeads to ongoing researchBenefits from scientific behavior
Science Checklist: Criteria for Science
7Where are the things we can study?Broad vs. Narrow questionsDo broad questions require simple or complex studies?Should we study broad or narrow questions?
Ch 2 Re-read thinking about these main ideas!
8Anything you are interested in can be studied if you properly develop questions into hypothesis. PASSION ASSIGNMENT
We are encouraging you to focus on narrow questions because larger questions require more complex design and analysis.
Ch 2 Experiments are everywhere!
9What are the types of measurement scales?Distinguish between nominal and ordinal scales.Distinguish between ratio and interval scales.Distinguish discrete data from continuous data.Why is it important to know what type of data you are collecting?
Ch 3 Re-read thinking about the following:
10Discrete Data - count data, answers questions about how many and how frequent. i.e. distributions of colors in a population of cats.Nominal unranked categories. Ordinal- ranked categories.Continuous data data measured on a scale. Answers questions about correlations, means, std. deviation, etc.Interval no true zero point (i.e. arbitrary zero point) I.e. Celsius.Ratio actual zero point ie: Kelvin scale
What are the types of measurement scales? More about this later!
11Most Information Least InformationRatio scale & Interval scale: Both of these can discuss correlations between the variablesOrdinal scale & discrete scale: These have less information & can only identify distributions within a population (how frequent or how many Information theory and types of data12The type of data you are collecting effects what type of answers you can find. Must collect data that is appropriate to answer the questions you ask.Correlations can only be studied with measurement dataDifferences can be studied with any of these data types.Why is it important to know what type of data you are collecting?
13Frequency histogramsMean, median and modeNormal distributionsMost importantly, that distributions within populations tend to be centered around a central value.
Ch 4. Re read it considering the following ideas:
14Why is it important to understand the spread of the data and not just the central tendency?
How do we measure the spread and what does it tell us?
Define variance and standard deviation.
CH.5 Re-read considering the following:
15Variance and standard deviation are very important because they quantify the spread of the data and allow us to compare two populations. You need to understand this more so check these links that might help.http://www.mathsisfun.com/standard-deviation.html http://sciencepolicy.colorado.edu/students/envs_5120/statistics_2_6.pdf Ch 5. Some thoughts16What is the null hypothesis?hypothesis that states there is no difference/ correlation between the variablesWhat is the change hypothesis?hypothesis that states there is a difference/ correlation between the variables
CH 6: Re-read considering the following:
17Determine your question Consider what type of data the question needsDefine the variables you are studyingWrite your hypothesisSet up data tablesAlign data collection with statistical test CH 6. What is a proper order for designing experiments? 18Notice only after all of this pre-work can you even hope to write a procedure. Remember the procedure has only one function; to collect good data! You cannot write or execute a procedure without a strong understanding of what your data will look like.
Now You Can Determine Your Materials 19What is the difference between correlation and difference testing?How much difference is necessary to say two populations are different?What is a confidence interval?What is the difference between parametric and nonparametric tests?When do you reject the change hypothesis? When do you reject the null hypothesis?
CH 7 Re-read this chapter focusing on the following:
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This is one of our focus topics during the class. Do your best to understand it and the first several days will include lectures on this topic. Cannot experiment without determining your method of data analysisRed flag: Here is my data. What statistical test do I use? Then I know you did not do slide # 17!!
CH 7: the Heart of Data Analysis 21