{"id":238,"date":"2025-07-01T02:03:48","date_gmt":"2025-07-01T02:03:48","guid":{"rendered":"https:\/\/pressbooks.hccfl.edu\/introchemlabmanual\/?post_type=chapter&p=238"},"modified":"2026-03-28T12:06:48","modified_gmt":"2026-03-28T12:06:48","slug":"post-lab-questions-4","status":"web-only","type":"chapter","link":"https:\/\/pressbooks.hccfl.edu\/introchemlabmanual\/chapter\/post-lab-questions-4\/","title":{"raw":"Post-Lab Questions","rendered":"Post-Lab Questions"},"content":{"raw":"

Directions:<\/h2>\r\nAnswer the following questions, show work for all calculations. Work must be shown to receive credit for calculations. All questions are weighted equally.\r\n
    \r\n \t
  1. If copper is known to have a density of 8.92 g\/cm3<\/sup>, determine the percent error between your experimental density of copper (by geometry & by displacement) and the known density of copper. Which measurement is more accurate? Explain.<\/li>\r\n \t
  2. If copper is known to have a density of 8.92 g\/cm3<\/sup>, determine the percent error & standard deviation of the class data set. Is the class data set accurate, precise, both, or neither?<\/li>\r\n \t
  3. Using a sheet of graph paper, draw a full-page bar graph displaying each of the experimental copper density values from the class data set. (Alternatively, use a spreadsheet program to plot this graph). Be sure your graph contains: Graph title, axis titles, and appropriate units.<\/li>\r\n \t
  4. Explain how you chose the identification of your unknown solid. What is the significance of density in identifying unknown materials?<\/li>\r\n \t
  5. Did your result differ from the theoretical value listed in the box? Identify 2 potential experimental sources of error.<\/li>\r\n<\/ol>\r\nNote: When explaining sources of error, avoid vague terms like \u201chuman error\u201d or \u201cexperimental error\u201d \u2014 instead, be specific about what happened. Errors in calculations or significant figures don\u2019t count because they can be checked and fixed before submitting your report. Don\u2019t list general balance calibration issues, since the equipment is regularly maintained.\u00a0 Focus on experimental factors during the lab that clearly affected your results.\r\n
    \r\n

    Licenses and Attribution<\/strong><\/h3>\r\n

    CC Licensed Content, Original<\/h4>\r\nThis educational material includes AI-generated content from ChatGPT by OpenAI. The original content created by Carol Stallworth from Hillsborough Community College is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0<\/a>).<\/span>\r\n\r\nAll images in this textbook generated with DALL-E are licensed under the terms provided by OpenAI, allowing for their free use, modification, and distribution with appropriate attribution.\r\n\r\n<\/div>\r\n ","rendered":"

    Directions:<\/h2>\n

    Answer the following questions, show work for all calculations. Work must be shown to receive credit for calculations. All questions are weighted equally.<\/p>\n

      \n
    1. If copper is known to have a density of 8.92 g\/cm3<\/sup>, determine the percent error between your experimental density of copper (by geometry & by displacement) and the known density of copper. Which measurement is more accurate? Explain.<\/li>\n
    2. If copper is known to have a density of 8.92 g\/cm3<\/sup>, determine the percent error & standard deviation of the class data set. Is the class data set accurate, precise, both, or neither?<\/li>\n
    3. Using a sheet of graph paper, draw a full-page bar graph displaying each of the experimental copper density values from the class data set. (Alternatively, use a spreadsheet program to plot this graph). Be sure your graph contains: Graph title, axis titles, and appropriate units.<\/li>\n
    4. Explain how you chose the identification of your unknown solid. What is the significance of density in identifying unknown materials?<\/li>\n
    5. Did your result differ from the theoretical value listed in the box? Identify 2 potential experimental sources of error.<\/li>\n<\/ol>\n

      Note: When explaining sources of error, avoid vague terms like \u201chuman error\u201d or \u201cexperimental error\u201d \u2014 instead, be specific about what happened. Errors in calculations or significant figures don\u2019t count because they can be checked and fixed before submitting your report. Don\u2019t list general balance calibration issues, since the equipment is regularly maintained.\u00a0 Focus on experimental factors during the lab that clearly affected your results.<\/p>\n

      \n

      Licenses and Attribution<\/strong><\/h3>\n

      CC Licensed Content, Original<\/h4>\n

      This educational material includes AI-generated content from ChatGPT by OpenAI. The original content created by Carol Stallworth from Hillsborough Community College is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0<\/a>).<\/span><\/p>\n

      All images in this textbook generated with DALL-E are licensed under the terms provided by OpenAI, allowing for their free use, modification, and distribution with appropriate attribution.<\/p>\n<\/div>\n

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