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RBIF-0103-G1 Probability and Statistics Prof. M. Partensky Brandeis University - Spring 2003

RBIF-0103-G1 Probability and Statistics Prof. M. Partensky Brandeis University - Spring 2003. Group Project Using Statistics and Mathematica to Analyze Body Temperatures. Vaishali Khamamkar Timothy Foley. Human Body Temperature as a Predictor of Ovulation.

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RBIF-0103-G1 Probability and Statistics Prof. M. Partensky Brandeis University - Spring 2003

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  1. RBIF-0103-G1 Probability and StatisticsProf. M. PartenskyBrandeis University - Spring 2003 Group Project Using Statistics and Mathematica to Analyze Body Temperatures Vaishali Khamamkar Timothy Foley

  2. Human Body Temperature as a Predictor of Ovulation • Tracking body temperature is part of an effective, low-tech. process that is used to predict ovulation • Many couples have difficulties in getting pregnant • There is a large body of online data posted, where women share their experiences, to help themselves and each other We thank them, and wish to treat their personal data with the utmost respect

  3. Technical Data and Measurements • The posted data is based upon daily measurements of a women’s body termperature • A Basal Body Temperature thermometer is used, accurate to 1/10° F • The captured data shows a statistical Time Series

  4. Results with Mathematica • We gathered 20-30 days of BBT data for 12 women • We plotted that data using: • ListPlot [ ], MultipleListPlot [ ] • We used anEpilogto show • Target Ovulation Date (Vertical Line) • Cover Line – Avg. Body Temp. (Horizontal Line) • 12 Graphs are displayed (Cyan Background)

  5. Data ManipulationSmoothing of Data • We wanted to smooth out the data in our results • A Rolling Mean metric is added, that calculates each day’s temperature as the average of: • Previous day’s BBT temperature • Current day BBT temperature • Next day’s BBT temperature • 12 new graphs are shown (light-green background): • Blank lines shown original plotted time series • Purple lines show smoothed Rolling Mean time series

  6. Results – BBT and Ovulation • All women show a rise in BBT values of 0.5°- 2.0° F. within one day of ovulation • We also note a BBT plateau, followed by a second rise in BBT, 3-5 days after ovulation • More information on this process is available at:http://www.babymed.com

  7. Concluding Remarks • We found several interesting areas of study related to body temperature • We learned things that we did not know or expect • Our knowledge of Statistics was broadened by this project • We found Mathematica to be a powerful and useful tool (once we got the hang of it!)

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