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What’s Covered

  • This lesson introduces the collection and evaluation of data, including:

    • Defining Data

    • Evaluating Types of Data

    • Gathering Data

Terms to Know

  • Data: Pieces of information used to answer statistical questions; can be numbers or attributes. It helps create a more accurate picture of a scenario.

1. Defining Data

  • Data is crucial for answering statistical questions.

  • It serves to provide accurate descriptions of scenarios and obtain insights.

  • Questions to reflect on data collection origins:

    • How is data obtained?

    • Where does it come from?

    • Is the data fabricated?

2. Evaluating Types of Data

  • Types of Data:

    • Available Data: Already collected and organized data, easier to access.

    • Raw Data: Unorganized, unprocessed, and not summarized data, typically generated by the user.

  • Sources of available data include:

    • Government organizations

    • Polling organizations

    • News sources

    • Private entities

  • Critical Evaluation: Always assess the credibility and context of the data:

    • Who collected the data?

    • Is the source reputable and trustworthy?

    • What was the collection time and method?

    • What intentions drove data collection?

  • Bias: Potential sources of bias can influence data interpretation, stemming from an organization’s agenda.

    • Bias is often unintentional but crucial to identify.

3. Gathering Data

  • If no existing data meets your question needs, you can collect data yourself.

  • Collecting your own data results in Raw Data which requires further processing before it’s useful.

  • Key Evaluation Questions for Data Gathering:

    • Who is the intended audience for the data?

    • Who will receive and access this data?

  • Importance of Data Quality:

    • Good data collection leads to accurate statistics.

    • Poor data collection results in poor statistics; it's detrimental to the overall analysis.

  • Big Idea: Quality of data directly influences the usefulness of statistical analysis.

Summary

  • Defined data as "information used in a study to answer a statistical question."

  • Evaluated data types: available and raw, emphasizing the critical thinking necessary to identify and mitigate bias.

  • Importance noted in understanding the data's audience and access in personal data gathering efforts.

Additional Terms to Know

  • Available Data: Data collected by another entity (government or private).

  • Bias: Systematic favoritism towards certain outcomes in research studies; numerous potential biases exist.