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STATISTICS FOR RESEARCH IN ECOLOGY

STATISTICS FOR RESEARCH IN ECOLOGY. By: Alexander Rodriguez. SHARKS. SEA TURTLES. MARINE DEBRIS. FREQUENCY OF SEA CIGAR LENGTHS. CORAL PLANULA. Probability- A way to measure the chances of something will occur in relation to the possible alternatives. Things that can kill coral

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STATISTICS FOR RESEARCH IN ECOLOGY

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  1. STATISTICS FOR RESEARCH IN ECOLOGY By: Alexander Rodriguez

  2. SHARKS

  3. SEA TURTLES

  4. MARINE DEBRIS

  5. FREQUENCY OF SEA CIGAR LENGTHS

  6. CORAL PLANULA • Probability- A way to measure the chances of something will occur in relation to the possible alternatives. • Things that can kill coral • Shallow depth in water (less than 150 ft) • Water temperature if it’s to cold (16-30°C or 61-76°F) • Boats go right over them and destroy them • Chemicals that get on them kill them • Wave action if it is very weak • Some don’t get enough sunlight so they die • Boat anchors crash them when they get thrown down

  7. VARIANCE AND STANDARD DEVIATIONS • Variance- The fact or quality of being different, divergent, or inconsistent. The formula is O². • Standard Deviation- How spread out the data are. The formula is O. • Example: If there are some dogs short or tall it would be a difference because the Rottweiler would be the biggest dog while all the other dogs like the terriers or dachshunds would be a lot shorter causing a difference in the mean.

  8. T.D.C. • Theoretical Distribution curve(bell)- A theoretical or ideal picture of a distribution based upon random spelling.

  9. T-TEST • T-test: An equation you will use to calculate the t-statistics which is a test designed to tell the significance between the two independent samples. • In the t-test it needs the mean, the number, and the variance. • If the t-test is higher than the p-value then you have to reject the null hypothesis. • In our case we had to because there was a significant difference.

  10. CHI-SQUARE • A chi-square test is a statistical test commonly used for testing independence and goodness of fit. • We played a sea turtle game to see how many turtles out of 100 will survive in the different beach sites. There were 500 turtle at first but by the end of the game 229 were left alive and 271 turtles died. • We finally rejected our null hypothesis, and accepted our alternative hypothesis because there was a significant difference in the survival rate at the different beach sites.

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