1. Cancer Characteristics Yemi Oso Scott Asplund Anthony Pico Josh Strauss

2. Abstract Analyze types of cancer and variables involved (6 leading cancers) How analyze data Architecture of analytics Analytics used Expectations Scope and limitation Conclusion

3. Introduction 1/3 Analyze cancer, looking at: –Cancer site, incidence rate, location and Mortality, Race, gender, Ethnicity, and age Look at raw data find trends overlooked unexpected Look in-depth data see location trends and cancer cure rates per type and location

4. Introduction 2/3 Cancer despite all research relatively unknown and not understood Cancer is the second leading cause of death behind heart disease (562,875 ) Lost/ family living with cancer providing drive to perform in depth analysis of data

5. Introduction 3/3: Why it is important 1/8 women suffer from breast cancer 1/13 men will develop lung cancer and 1/16 women will 1/6 men will develop prostate cancer The numbers speak for themselves, cancer is a major problem, we must learn

6. Problem Statement Find trends in cancer as to cancer location, race, age, gender, ethnicity, and cure rates of cancer –Look for correlation between Cancer site and Mortality, Location, Race, gender, Ethnicity, and age –Look for correlation between incidence rate and Location, Race, Sex, Ethnicity, and age –Look for a correlation between Location and Race, gender, Ethnicity, and age

7. Scope and Limitations Work within the CDC “WoW” database and given information. Cancer data between 2002 and 2006 within U.S. Cannot go outside of the given data and information (See previous slides) Look at 6 prevalent cancer types