{"id":402,"date":"2025-02-19T16:46:45","date_gmt":"2025-02-19T16:46:45","guid":{"rendered":"https:\/\/integrations.pressbooks.network\/steel\/?post_type=chapter&p=402"},"modified":"2025-02-19T17:07:04","modified_gmt":"2025-02-19T17:07:04","slug":"broken-chapter","status":"publish","type":"chapter","link":"https:\/\/integrations.pressbooks.network\/steel\/chapter\/broken-chapter\/","title":{"raw":"Broken Chapter","rendered":"Broken Chapter"},"content":{"raw":"
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Learning Objectives<\/h3>\r\n
    \r\n \t
  1. Distinguish between descriptive and inferential statistics<\/li>\r\n \t
  2. Identify the different kinds of descriptive statistics researchers use to summarize their data<\/li>\r\n \t
  3. Describe\u00a0the purpose of inferential statistics.<\/li>\r\n \t
  4. Distinguish between Type I and Type II errors.<\/li>\r\n<\/ol>\r\n<\/div>\r\nOnce the study is complete and the observations have been made and recorded the researchers need to analyze the data and draw their conclusions. Typically, data are analyzed using both descriptive and inferential statistics. Descriptive statistics are used to summarize the data and inferential statistics are used to generalize the results from the sample to the population. In turn, inferential statistics are used to make conclusions about whether or not a theory has been supported, refuted, or requires modification.\r\n

    Descriptive Statistics<\/h2>\r\nDescriptive statistics are used to organize or summarize a set of data. Examples include percentages, measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation, variance), and correlation coefficients.\r\n\r\nMeasures of central tendency are used to describe the typical, average and center of a distribution of scores. The [pb_glossary id=\"909\"]mode[\/pb_glossary]<\/strong> is the most frequently occurring score in a distribution. The [pb_glossary id=\"910\"]median[\/pb_glossary]<\/strong> is the midpoint of a distribution of scores. The [pb_glossary<\/span> id=\"911\"]mean[\/pb_glossary]<\/strong> is the average of a distribution of scores.","rendered":"
    \n

    Learning Objectives<\/h3>\n
      \n
    1. Distinguish between descriptive and inferential statistics<\/li>\n
    2. Identify the different kinds of descriptive statistics researchers use to summarize their data<\/li>\n
    3. Describe\u00a0the purpose of inferential statistics.<\/li>\n
    4. Distinguish between Type I and Type II errors.<\/li>\n<\/ol>\n<\/div>\n

      Once the study is complete and the observations have been made and recorded the researchers need to analyze the data and draw their conclusions. Typically, data are analyzed using both descriptive and inferential statistics. Descriptive statistics are used to summarize the data and inferential statistics are used to generalize the results from the sample to the population. In turn, inferential statistics are used to make conclusions about whether or not a theory has been supported, refuted, or requires modification.<\/p>\n

      Descriptive Statistics<\/h2>\n

      Descriptive statistics are used to organize or summarize a set of data. Examples include percentages, measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation, variance), and correlation coefficients.<\/p>\n

      Measures of central tendency are used to describe the typical, average and center of a distribution of scores. The mode<\/strong> is the most frequently occurring score in a distribution. The median<\/strong> is the midpoint of a distribution of scores. The mean<\/strong> is the average of a distribution of scores.<\/p>\n

      definition<\/span>