{"id":491,"date":"2022-07-11T19:04:06","date_gmt":"2022-07-11T19:04:06","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/alphamodule\/?post_type=chapter&p=491"},"modified":"2022-08-04T20:22:10","modified_gmt":"2022-08-04T20:22:10","slug":"interpreting-the-mean-and-median-of-a-dataset-apply-it-2","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/alphamodule\/chapter\/interpreting-the-mean-and-median-of-a-dataset-apply-it-2\/","title":{"raw":"Interpreting the Mean and Median of a Dataset: Apply It 2","rendered":"Interpreting the Mean and Median of a Dataset: Apply It 2"},"content":{"raw":"

Misleading Claims<\/h2>\r\nThe actual median salary among Texas NBA players was $[latex]1,577,320[\/latex] while the mean salary was $[latex]5,262,279[\/latex].
Use this information to complete Questions 4-6:\r\n
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question 4<\/h3>\r\n[ohm_question hide_question_numbers=1]257423[\/ohm_question]\r\n\r\n[reveal-answer q=\"594557\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"594557\"]Consider the scale of the dotplot. The median should be between 1 and 2 million and the mean should be just above 5 million.[\/hidden-answer]\r\n\r\n<\/div>\r\n
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question 5<\/h3>\r\n[ohm_question hide_question_numbers=1]257424[\/ohm_question]\r\n\r\n[reveal-answer q=\"319249\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"319249\"]To find an exact percentage, you can count the number of data points above each value and divide by the total number of players, 61.[\/hidden-answer]\r\n\r\n<\/div>\r\n
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question 6<\/h3>\r\n[ohm_question hide_question_numbers=1]241110[\/ohm_question]\r\n\r\n[reveal-answer q=\"17406\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"17406\"]Think about how the outliers affect the mean and median.[\/hidden-answer]\r\n\r\n<\/div>\r\n
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video placement<\/h3>\r\n[Guidance: \"Consider your answers to Questions 3 - 6. [voice over images of the dotplot with the vertical lines drawn] What did you consider to be a \"typical\" salary? What characteristic of this variable's distribution caused the mean to be different from the median?\"]<\/span>\r\n\r\n<\/div>\r\nNow consider the following scenario.\u00a0An NBA recruiter for the Houston Rockets approaches a promising college basketball player and says, \u201cthe typical salary among Texas NBA players is $[latex]5,262,279[\/latex].\u201d\r\n
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question 7<\/h3>\r\n[ohm_question hide_question_numbers=1]241111[\/ohm_question]\r\n\r\n[reveal-answer q=\"523741\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"523741\"]Use what you know about sensitivity to skew\/outliers.[\/hidden-answer]\r\n\r\n<\/div>\r\n
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video placement<\/h3>\r\n[insert a sub-summary here. \"How did you your answer the question, \"is the recruiter's statement misleading?\" Did you consider the mean to be a \"typical\" salary among these NBA players? What could the recruiter have said instead? That it is\u00a0likely\u00a0<\/em>a player would make $5.3 million by joining the team? That is is\u00a0possible\u00a0<\/em>for some highly skilled and talented players? Or would it have been less misleading for the recruiter to have emphasized the median salary of $1.58 million? If you were in the prospective player's position, would you have asked to see the distribution to make your own assessment? Which value would you have used, mean or median, if you were in the recruiter's position?\"]<\/span>\r\n\r\n<\/div>\r\nYou've seen that the mean, under certain conditions, can be a misleading indicator of a \"typical\" observation value, such as the salary of a professional basketball player. Now try to apply this understanding to some other types of data collections.","rendered":"

Misleading Claims<\/h2>\n

The actual median salary among Texas NBA players was $[latex]1,577,320[\/latex] while the mean salary was $[latex]5,262,279[\/latex].
Use this information to complete Questions 4-6:<\/p>\n

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question 4<\/h3>\n