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Understanding Statistics: Data Science and Art for Real-World Insights

Delve into the world of statistics as the science and art of collecting, presenting, and interpreting data to draw meaningful conclusions. Learn about the importance of non-mathematical ideas in statistical studies, data collection methods, and the significance of random sampling in surveys and polls. Explore the concepts of bias and precision to ensure accurate representation and interpretation of data in statistical investigations.

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Understanding Statistics: Data Science and Art for Real-World Insights

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  1. Chapter 1 What is Statistics?

  2. Chapter 1 - What is Statistics? A couple of definitions: Statistics is the science of data. Statistics is the science and art of collecting, presenting, describing and drawing conclusions from data.

  3. Chapter 1 - What is Statistics? • “The subject matter of statistics is the process of finding out more about the real world by collecting and making sense out of data” • This course • is not just about doing statistical calculations • it is also about non-mathematical ideas • (about 50% of the course)

  4. Chapter 1 - What is Statistics? • Non-mathematical ideas are at least as important as technical skills for • successful completion of statistical studies in real life • success in this course

  5. Design method of data collection Real problems Curiosity Pose the question Answer to original question Collect Data Summary and analysis of data Interpret the results What do they mean? The Cycle Of Statistical Investigation

  6. Surveys and Polls Observational Studies Experimentation Design Method of Data Collection

  7. Polls and Surveys A pollor a survey is the process of collecting data from a sample, or subset, of the population in order to determine information about the whole population.

  8. Polls and Surveys Why Sample? • “You don’t have to eat the whole ox to know that the meat is tough” • Samuel Johnson

  9. Polls and Surveys Why Sample? • Cheaper • Faster • Practicality • access to the population may be difficult or impossible • Accuracy • control of interviewers • collating information

  10. Polls and Surveys Why Sample? Our goal would be to have a sample that reflects the variation that the whole population exhibits, especially in terms of characteristics that may have an effect on whatever we wish to measure. We call such a sample “representative”.

  11. Randomization In Surveys • Surveys should use some form of random sampling to obtain a representative sample. Random sampling: • ensures each person / item has an equal chance of being chosen in a given draw • avoids subjective and other biases • allows for calculation of likely size of sampling errors Note: The larger the sample, the more effective the randomization in producing a representative sample.

  12. Bias and Precision High bias, high precision Low bias, low precision Low bias, high precision (our aim!) High bias, low precision

  13. High bias, high precision Low bias, low precision Low bias, high precision (our aim!) High bias, low precision Bias and Precision Where: Bias is consistent repeated departure of the sample results in the same direction and Lack of precision is when in repeated sampling the values are spread out or scattered.

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