Announcements:-- EXAM NEXT WEEK

Wednesday, February 11, 12:15 pm, COM—SPECIAL SEMINAR, "Deciphering the X in sex: from genomic mechanisms to phenotypic implications," Dr. Laura Carrel, Pennsylvania State University, University Park.

Thursday, February 12, 7:00 pm, FSU Coastal and Marine Laboratory Auditorium, St. Teresa, Florida—COASTAL AND MARINE CONSERVATION LECTURE, "Ecological and evolutionary misadventures with Spartina," Dr. Donald R. Strong, University of California, Davis. Refreshments will be provided.

Friday, February 13, 11:30 am, 2057 KIN—SPECIAL BIOLOGICAL SCIENCE SEMINAR, "Top down from underground: diseases of root-feeding insects," Dr. Donald R. Strong, University of California, Davis. Host:

Friday, February 13, 2:00 pm, 327 OSB—BIOLOGICAL OCEANOGRAPHY SEMINAR, "Love and jealousy in sea urchins: sexual selection and the evolution of gamete recognition proteins," Dr. Don R. Levitan, Department of Biological Science, FSU

Friday, February 13, 4:00 pm, 1024 KIN—ECOLOGY AND EVOLUTION SEMINAR, "Reduced freshwater input leads to increased disease, predation, and mortality in Apalachicola oysters," Dr. Laura E. Petes, FSU Coastal and Marine Laboratory.

H: males and females have different numbers of Facebook FriendsH0: males and females have the same number of Facebook Friends

€

t =x1 − x2( )

n1 −1( )s12 + n2 −1( )s2

2

n1 + n2 − 21n1

+ 1n2

Mean S2 NFemale 5.13 4.79 43

Male 5.61 2.05 24

t = -1.0886; df = n1 + n2 -2 = 65

The critical value for t is 2.00, so we cannot reject our null hypothesis

Visit Library Not Visit Library

Female 33 10Male 21 3

H = different proportions of males and females have visited the libraryH0 = equal proportions of males and female have visited the library

€

χ 2 =(observed - expected)2

expected∑

Visit Library Not Visit Library

Female 33 10Male 21 3

Visit Library

Not Visit Library

Female 33 (34.66) 10 (8.34) 43Male 21 (19.34) 3 (4.66) 24

54 13 67

X2=0.555, with df = (2-1)(2-1) = 1

The test statistic is 3.8, so we cannotreject our null hypothesis.

5. (4 pts.) We want to know if red cars or blue cars are involved more in accidents..a. Clearly state a testable hypothesis and a null hypothesis

H1: Red cars are involved in a different number of accidents than blue cars (or one is great thenthe other is OK).

H0: Red and blue cars are involved in an equal number of accidents.

b. Describe an observation test that could discriminate between these hypotheses.

Watch cars on Tennessee street until 100 accidents have been observed. Compare number ofaccidents using chi-square test of 50/50 ratio.

Other designs for tests are possible, such as checking junk yard or police or insurance records.

c. Would a true experiment be a better, equal, or worse than the observational study in thiscase? Explain your answer.

An experimental study is always better, if possible. In this case, you could take 100 peopleand randomly assign them a blue or red car, then check ontheir accident rate 30 days later, forexample. The explanation is that observational studies cannot control all factors, so that anycorrelation between car color and accident rate is not causal. Everyone got full credit for this poorlydesigned question.

6. (6 pts) We set up a tub with apples for an apple bobbing contest to see if apple densitychanges how people forage for apples. The tub contains 15 apples floating in water: 5 small redapples that float, 5 large red apples that sink, and 5 large yellow apples that float. We have 5men bob for apples in this tub, replacing any apples that are taken between students. Their goalis to collect the most apples per unit time.

We then empty out the tub and set it up again. However, this time, we double the number ofapples of each type in the tub, with 10 of each type. We have five women now bob for apples,exactly as before, maximizing their apples per time.

a. Help us out: provide a null and test hypothesis that can reasonably be addressed with thisdata..H1: foraging rates (or specialization) changes with the density of apples.H0: there is no effect of the number of apples on foraging rate or specificity.

For the following questions, assume that we obtained the following data after adding up theresults for all five students in each trial:

Small red Large red Large yellowLow density 10 5 35High density 2 0 48

b. Provide a rough graph illustrating these results, using the correct format.

(depends on H, 1 1/2 points)

Could be bar graph showingmeans with error bars for twogroups (continuous) or lots ofbars showing frequency ornumber by “type” (discrete data)

c. Set the above data in the proper statistical equation. You do not have to actually solve theequation -- just set it up properly.

1 point. Needed to be chi-square for discrete, t test for continuous

(10 – exp)2/exp + (5 – exp)2/exp +(35 – exp)2/exp +(2 – exp)2/exp +(0 – exp)2/exp+(48 –exp)2/exp = chi square value

0

10

20

30

40

50

60

small red large red large yellow

Type of Apple

Number of Apples

"bobbed"

low densityhigh density

d. Assume that the test value obtained using the data was 12.4. We will put the appropriate tableup on the screen. Answer the following questions.

What are the appropriate degrees of freedom?2 for chi-square (1/2 point)

What conclusions can you draw from this experiment (must relate properly back to yourhypotheses!).

2 points. One point for stating that you can reject the null hypothesis because the test value wasgreater than the critical value. One point for interpreting this in light of the original question andhypotheses.

e. Tell me two flaws in this experimental design.

1 point each

-- confounded treatment with gender-- confounded treatment with time

Plagiarism 

Plagiarism or the use of literal material from the scientific literature is prohibited under most circumstances and violates the FSU Student Honor Code. Do not quote from articles: instead figure out what they have written and interpret it in your own words. Follow your interpretation with a proper citation. Even enclosing material in quotes is generally unacceptable unless, for some reason, you could not write this information in your own words. Your TA’s have been instructed to conduct electronic searches to look for plagiarism if they have any concerns about the writing in your proposals or papers.

II. ProposalsIncludes most of what goes into a regular paper, but in summary form.We have changed to format somewhat from your final paper to focus onthe scientific method.

III. Full papers (p. 53)

A. Title – make informative and specific

Vague: Foraging behavior in ants

Specific: Effects of prey size on foraging rate in the fireant, Solonopsisinvicta

Wordy: A study of the importance of prey size on the amount of preytaken by fireants of the species Solonopsis invicta near Tallahassee,Florida

B. Abstract – write last. Be specific, but concise. Leave out virtually allintroduction and methods. Great examples in book on page 57-61.

C. Introduction -- must orient reader, explain rationale for thestudy and ultimately set out the hypotheses addressed. Vstructure, from general to specific

D. Materials and methods –be explicit enough that another studentcould repeat your study in all important essentials.

So, if you feed birds seeds as part of your study, you would want to say thatthey were sunflower seeds, you used 40 seeds per tray, and that you fedthem to birds from 6 to 8 AM. You wouldn’t need to tell us that they werepurchased at Publix in a plastic bag and that you counted them by hand.

E. Results – summarize and illustrate your findingsReally pretty easy, but may be very short on text. That is OK for this class.The biggest problems people have is keeping out methods anddiscussion. Results should not have interpretation or conclusions.

F. Discussion -- back right out of the V created in the Introduction. MacMillangives four clear steps, in order.

1. State your major findings ,.2. Tell us what causes may underlie these results. If results seems

surprising or contradictory, suggest explanations.3. Compare your findings with the work of other researchers.4. A conclusion paragraph isn’t used – that is what the abstract is

for. Instead, the last paragraph should have far-reaching predictions andinterpretations. Why would a scientist in some broader field care (orperhaps a classmate!) .

G. Literature Cited.No excuse not to get this correct. Lab manual provides many

examples.