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Calculate the number of colors issued per year. Add a comment to your code stating in which year the largest number of colors were issued.

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Download the SAS data set named CRAYONS from Canvas and save it to your local machine. This data set contains information on standard Crayola crayon colors. The variables in this file are crayon number, color name, hexadecimal code, RGB triplet, pack added, year issued, and year retired.

  1. In a comment in your code, describe two different ways that you could view the variable attributes in this SAS data set.
  2. Using one of the methods described in part a), review the names, labels, and attributes of the variables in the SAS data set CRAYONS. Record the label and length for the variable Color as a comment in your program.


  3. Calculate the number of colors issued per year. Add a comment to your code stating in which year the largest number of colors were issued.


  4. Sorting the crayons by color using their names would be ineffective due to the uniqueness of the names, but the information found in the RGB triplets can be used instead. Sort the crayon data by RGB triplet.


  5. Print the sorted data showing only columns for the variables color name and RGB triplet.

 

Problem 2 (20 Points).

 

Download the SAS data set named SFF from Canvas and save it to your local machine.

 

The World Health Organization (WHO) collected data in countries across the world regarding the outbreak of swine flu cases and deaths in 2009. The SAS data set called SFF includes information on cases and deaths per country by month during the epidemic.

 

  1. Review the names, labels, and attributes of the variables in the SAS data set SFF. Record the name and length of the character variables as a comment in your program.


  2. Count the number of countries within each continent.


  3. Count the number of countries per continent that reported no cases during the first month of the outbreak (April) versus the number of countries per continent that had at least one case. Do the same for the last month of the outbreak (August).


  4. To find potential errors in the data, create a report for countries that reported a first death date, but reported no first case date. This output should include only the variables continent, country, first case date, last reported number of cases, and first death date.


  5. Add code that will organize the report from part d) so that the countries on the same continent are grouped together, and make sure that dates are presentable.

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