Homework 10

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Georgia Institute Of Technology *

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2400

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Health Science

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Dec 6, 2023

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docx

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5

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Name: Rebecca Fisher Collaborators 1 : Beth Patterson Basic information Topics covered: Logistic regression. Assigned: 11/14 Due: 11/21 Data notes: No external data is needed to answer the questions. Submission: Please submit via Canvas. Submit one word or pdf file, with each problem starting on a new page. Put all code, figures, and work in the word/pdf document. 1 Please list anyone you worked with on the homework. This uses the honor system. Remember that I encourage you to work together but that the work your turn in should be your own work.
Problem 1: Suzuki et al. (2006) measured sand grain size on 28 beaches in Japan and observed the presence or absence of the burrowing wolf spider Lycosa ishikariana on each beach. Sand grain size is a measurement variable, and spider presence or absence is a nominal variable. At what grain size, the odds of seeing a spider is 1 to 3. If the sand grain size is increased 0.05 mm, how will the odds of seeing a spider be affected, explain your work. a) Equations: Odds= P/(1-P) = 1/3 Ln[Y/(1-Y)]= β 0 + β 1 x 1 X 1 = (ln(P/1-P) - β 0 )/ β 1 Calculations: Logistic regression in excel (x-var= grain size, y-var= spiders(presence) X 1 = ln(1/3) +1.255/ 4.40927 .0355 Analysis: At a grain size of .0355mm the odds of seeing a side is 1/3 b) Equations: Estimated regression equation: P = e B 0 + B 1 x 1 1 + e B 0 + B 1 x 1
Calculations: Logistic regression in excel with all sizes+.05 mm (x-var= grain size +.05, y-var= spiders(presence) P= = grain ¿¿ ¿ − 1.6476 + 5.1215 ¿ 1 + e ¿ e − 1.6476 + 5.1215 ( grainsize ) ¿ grain size =.0355 .2109 Analysis: In the shifted model the odds of seeing a spider at grain size .035 decreased to about 1 to 5.
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