Dataset Information 1. Name of the Dataset: Bachelor Degrees Conferred by Race and Ethnicity Source of the Data: National Center for Education Statistics (NCES) Variable Selection 1. Variable for Frequency Table: Race/Ethnicity (categorical variable) • Type of Variable: Nominal • Rationale for Choice: ■Race/Ethnicity represents categories without inherent order (i.e., White, Black, Hispanic, etc.). Class Organization for Frequency Table ⚫ Creating Classes: • Each class corresponds to a specific racial/ethnic category. • For example: ■ Class 1: White ■ Class 2: Black ■ Class 3: Hispanic ■ Class 4: Asian/Pacific Islander • Class Limits: Class 5: American Indian/Alaskan Native • Yes, there would be class limits, as the classes are distinct categories that can encompass specific counts from the dataset. Cumulative Relative Frequency ⚫ Meaningful Cumulative Relative Frequency: • Yes, cumulative relative frequency can have significance here as it can show the cumulative percentage of bachelor degrees conferred across different racial/ethnic groups, providing insight into representation trends over time. Summary • The dataset "Bachelor Degrees Conferred by Race and Ethnicity" is sourced from NCES. ⚫ A nominal variable, race/ethnicity, can be used to create a frequency table with specific classes for different racial/ethnic categories. • Class limits exist due to distinct categories, and cumulative relative frequency can illustrate representation trends effectively over different groups. Year White Black Hispanic Asian Pacific Islander American Indian/Alaskan Native ■ 2000 929,102 108,018 2001 2002 75,063 927,357 111,307 77,745 958,597 116,623 12,966 77,909 8,717 78,902 9,049 83,093 9,165 2003 994,616 124,253 2004 1.026.114 131.241 89,029 87,964 9.875 94,644 92.073 10.638 2005 1,049,141 136,122 101,124 97,209 10.307 2006 1,075,561 142,420 107,588 102,376 10,940 2007 1,099,850 146,653 114,936 105,297 11,455 2008 1,122,675 152,457 123,048 109,058 11,509 2009 1,144,628 156,603 129,473 112,581 12.221 2010 1,167,322 164.789 140,426 117,391 12.405 2011 1,182,690 172,731 154,450 2012 1,212,417 185,916 169,736 121,118 11.935 126,177 11,498 2013 1,221,908 191,233 186,677 130,129 11,432 2014 1,218,998 191,437 202,425 2015 1,210,071 192.829 216,098 2016 1,197,399 194,473 131,662 10,784 133,916 10,200 235.014 138,270 9.737 MAIN POST: Review your initial post from Unit 1. Think about the type of data analyzed using a frequency table. What are some other ways that the data could be analyzed? 1. Identify which of the following methods can be used for further analysis of your data. Explain why you know that type of analysis is possible. a. Mean b. Median c. Mode d. Range e. Variance f. Standard Deviation g. Box plot 2. Choose a method identified in part 1. What does that information tell you about the data?

Dataset Information 1. Name of the Dataset: Bachelor Degrees Conferred by Race and Ethnicity Source of the Data: National Center for Education Statistics (NCES) Variable Selection 1. Variable for Frequency Table: Race/Ethnicity (categorical variable) • Type of Variable: Nominal • Rationale for Choice: ■Race/Ethnicity represents categories without inherent order (i.e., White, Black, Hispanic, etc.). Class Organization for Frequency Table ⚫ Creating Classes: • Each class corresponds to a specific racial/ethnic category. • For example: ■ Class 1: White ■ Class 2: Black ■ Class 3: Hispanic ■ Class 4: Asian/Pacific Islander • Class Limits: Class 5: American Indian/Alaskan Native • Yes, there would be class limits, as the classes are distinct categories that can encompass specific counts from the dataset. Cumulative Relative Frequency ⚫ Meaningful Cumulative Relative Frequency: • Yes, cumulative relative frequency can have significance here as it can show the cumulative percentage of bachelor degrees conferred across different racial/ethnic groups, providing insight into representation trends over time. Summary • The dataset "Bachelor Degrees Conferred by Race and Ethnicity" is sourced from NCES. ⚫ A nominal variable, race/ethnicity, can be used to create a frequency table with specific classes for different racial/ethnic categories. • Class limits exist due to distinct categories, and cumulative relative frequency can illustrate representation trends effectively over different groups. Year White Black Hispanic Asian Pacific Islander American Indian/Alaskan Native ■ 2000 929,102 108,018 2001 2002 75,063 927,357 111,307 77,745 958,597 116,623 12,966 77,909 8,717 78,902 9,049 83,093 9,165 2003 994,616 124,253 2004 1.026.114 131.241 89,029 87,964 9.875 94,644 92.073 10.638 2005 1,049,141 136,122 101,124 97,209 10.307 2006 1,075,561 142,420 107,588 102,376 10,940 2007 1,099,850 146,653 114,936 105,297 11,455 2008 1,122,675 152,457 123,048 109,058 11,509 2009 1,144,628 156,603 129,473 112,581 12.221 2010 1,167,322 164.789 140,426 117,391 12.405 2011 1,182,690 172,731 154,450 2012 1,212,417 185,916 169,736 121,118 11.935 126,177 11,498 2013 1,221,908 191,233 186,677 130,129 11,432 2014 1,218,998 191,437 202,425 2015 1,210,071 192.829 216,098 2016 1,197,399 194,473 131,662 10,784 133,916 10,200 235.014 138,270 9.737 MAIN POST: Review your initial post from Unit 1. Think about the type of data analyzed using a frequency table. What are some other ways that the data could be analyzed? 1. Identify which of the following methods can be used for further analysis of your data. Explain why you know that type of analysis is possible. a. Mean b. Median c. Mode d. Range e. Variance f. Standard Deviation g. Box plot 2. Choose a method identified in part 1. What does that information tell you about the data?

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section: Chapter Questions

Problem 9SGR

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