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Cancer A Global View Claudia Neuhauser University of Minnesota Rochester Learning Objectives After completion of this module, the student will be able to explore social, economic and environmental development at local, national and


  1. Cancer A Global View Claudia Neuhauser University of Minnesota Rochester

  2. Learning Objectives • After completion of this module, the student will be able to – explore “social, economic and environmental development at local, national and global levels” with Gapminder – perform and interpret logarithmic transformations for graphical display – download global health data from Gapminder and WHO

  3. Knowledge, Skills, Prerequisites • Knowledge and Skills – logarithmic transformation – continuous time population models – fitting a trendline to data • Prerequisites – calculating percent changes – straight lines – natural logarithm, exponential function – graphing in EXCEL

  4. Key Facts (WHO) Cancer is a leading cause of death worldwide: it • accounted for 7.4 million deaths (around 13% of all deaths) in 2004. Lung, stomach, colorectal, liver, and breast cancer • cause the most cancer deaths each year. The most frequent types of cancer differ between • men and women. More than 30% of cancer deaths can be • prevented. Tobacco use is the single most important risk • factor for cancer. Source: World Health Organization: http://www.who.int/mediacentre/factsheets/fs297/en/

  5. explore “social, economic and environmental development at local, national and global levels” with Gapminder LEARNI NG OBJECTI VE 1

  6. Gapminder • Gapminder “is a non-profit venture promoting sustainable global development and achievement of the United Nations Millennium Development Goals by increased use and understanding of statistics and other information about social, economic and environmental development at local, national and global levels.” • I n-class Activity 1 • Watch the following video in Gapminder:

  7. Exploring Gapminder • In-class Activity 2 (see handout)

  8. perform and interpret logarithmic transformations for graphical display LEARNI NG OBJECTI VE 2

  9. Logarithmic Transformations Avg # of seeds Seeds per planted reproducing per sqm individual 1 11660 5 2700 45 228 100 128 205 64 • log-log plot

  10. Logarithmic Transformations NumberOfMonkParake Year etsPerPartyHour(effort) 76 0.03 77 0.031 78 0.035 79 0.027 80 0.041 81 0.048 82 0.026 83 0.048 84 0.064 85 0.083 86 0.177 87 0.121 88 0.234 89 0.2 90 0.393 91 0.414 • log-linear, or semi-log, plot 92 0.436 93 0.387 94 0.387 95 0.501

  11. In-class Activity 4a • Go to your spreadsheet (Tab 1: Plantain) and reproduce the first graph using the Plantain data in the spreadsheet. • Go to your spreadsheet (Tab 2: Parakeet) and reproduce the second graph using the Parakeet data in the spreadsheet.

  12. The Logarithmic Scale x 0.01 0.1 1 10 100 1000 Log x -2 -1 0 1 2 3 • In-class Activity 3 – On the two axes above find the following numbers: x= 0.05, 0.2, 8, 15, 750. – Why do you think we choose logarithms to base 10, instead of some other base? – Can you plot negative numbers on a logarithmic scale? – As x approaches 0, where would you find x on a logarithmic scale?

  13. The Logarithmic Scale x 0.01 0.1 1 10 100 1000 Log x -2 -1 0 1 2 3 • In-class Activity 3 – On the two axes above find the following numbers: x= 0.05, 0.2, 8, 15, 750. • Log 0.05= -1.30 • Log 0.2= -0.699 • Log 8= 0.903 • Log 15= 1.176 • Log 750= 2.875

  14. The Logarithmic Scale x 0.01 0.1 1 10 100 1000 Log x -2 -1 0 1 2 3 • In-class Activity 3 – On the two axes above find the following numbers: x= 0.05, 0.2, 8, 15, 750. – Why do you think we choose logarithms to base 10, instead of some other base? – Can you plot negative numbers on a logarithmic scale? – As x approaches 0, where would you find x on a logarithmic scale?

  15. In-class Activity 4b • Fit an appropriate function to the Plantain data in the spreadsheet. • Fit an appropriate function to the Parakeet data in the spreadsheet.

  16. Logarithmic Transformations Avg # of seeds Seeds per planted reproducing per sqm individual 1 11660 5 2700 45 228 100 128 205 64 • log-log plot • Go to your spreadsheet and fit a trendline

  17. Case 1: Both axes are logarithmically transformed If both axes are logarithmically transformed and a straight line results, then the relationship between x and y y  a is a power function : bx

  18. Logarithmic Transformations NumberOfMonkParake Year etsPerPartyHour(effort) 76 0.03 77 0.031 78 0.035 79 0.027 80 0.041 81 0.048 82 0.026 83 0.048 84 0.064 85 0.083 86 0.177 87 0.121 88 0.234 89 0.2 90 0.393 91 0.414 log-linear, or semi-log, plot • 92 0.436 93 0.387 Go to your spreadsheet and fit a • 94 0.387 trendline 95 0.501

  19. Case 2: The x-axis is on an arithmetic scale and the y-axis is logarithmically transformed If the x -axis is on an arithmetic scale and the y -axis is logarithmically transformed and a straight line results, then the relationship between x and y is an exponential function : y  x ca

  20. download global health data from Gapminder and WHOSIS LEARNI NG OBJECTI VE 3

  21. Downloading Data from Gapminder

  22. World Health Organization • “The Global Health Observatory (GHO) is WHO's portal providing access to data and analyses for monitoring the global health situation. It provides critical data and analyses for key health themes, as well as direct access to the full database. The GHO presents data from all WHO programmes and provides links to supporting information.” • http://www.who.int/whosis/en/ • http://apps.who.int/ghodata/

  23. Downloading Data from WHO

  24. EXPLORE THE WHO WEBSI TE

  25. Group Project—Summative Assessment Does the price of tobacco products affect lung cancer • rates? Go to MashupCigarettesGDPCancer.xls • The mashup of data from the CDC, World Health • Organization (WHO), and Gapminder provides data for select countries on the following three indicators: – price of 100 packs of cigarettes as a percentage of GDP per capita, – the per capita GDP for select years, – lung cancer rates in men and women for a single year. Use the data to investigate the relationship between the • three indicators.

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