Due in 6 hours- programming HW (MUST BE ABLE TO USE SAS SOFTWARE)

STAT 480 Assignment #2 (Due July 20th, Wednesday, 11:59 PM)

Instructions: Read lectures notes and sample codes I used in class carefully before starting your homework. You need to submit a .sas file on ANGEL (Lessons > Homework > dropbox for Homework2).

1. (Column Input and Assignment Statement). Below is a small dataset of grades for 6 students.

Name Gender Homework Midterm Final Beck Male 90 88 75 Christal Female 100 85 80 Gavetti Female 80 77 71 Easton Male 90 82 76 Mattiace Male 60 67 53 Chen Female 85 83 68

Table 1: Grades

(a) Use column input to read the dataset above called Grades and store it in the folder MyLibrary1 (the same folder we used for assginment#1, X:/STAT480/SAS library/MyLibrary1).

(b) Define Two new variables Score1 and Score2, where Score1 = 40% Homework +20% Midterm + 40% Final, and Score2 = 40% Midterm + 60% Final.

(c) Calculate the final score. The final score, represented by a new variable fs, is defined to be the maximum of the following three variables: Final, Score1 and Score2.

(d) Curve the final score fs. The curved new final score, represented by newfs, is defined as

newfs = 0.7 × fs + 30

(e) Round the new final score newfs to the nearest multiple of 5. (Hint: Use round function, round(argument1, argument2), read SAS documentation for more details.)

(f) Print out the whole dataset, including all the new variables you created except the variable Gender. (Use var statement).

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2. (Formmated Input). Below is a dataset of all the games between Argentina and Germany in the FIFA World Cup. The descriptions of the variables are:

• game: the number of the game

• year: the year of the World Cup

• date: the date of the game

• stage: the stage of the game (a character variable)

• Arg: the score of Argentina

• Ger: the score of Germany

• Attendence: the number of audience

game year date stage Arg Ger Attendance 1 1958 08Jun1958 1st Round, Group1 1 3 31,156 2 1966 16Jul1966 1st Round, Group2 0 0 46,587 3 1986 29Jun1986 Final Game 3 2 114,600 4 1990 08Jul1990 Final Game 0 1 73,603 5 2006 30Jun2006 1/4 Finals 1 1 72,000 6 2010 03Jul2010 1/4 Finals 0 4 64,100 7 2014 13Jul2014 Final Game 0 1 74,738

Table 2: Germany vs Argentina in World Cup

(a) Use formatted input to read the dataset above called games. When reading the dataset (1) use an absolute pointer control to read year and date, and use a relative pointer controls to read stage and Attendance; (2) Use informat dateW. for variable ’date’ and use informat commaW. for variable ’Attendance’, where W is an integer which specifies the number of columns that variable will occupy.

(b) Set the page size to 50, line size to 80, center the output, and suppress the date and time when the output was created.

(c) Print the data set games. (1) Remember formatted input does not imply formatted output. Use format statement to format your output; (2) Add a title for this dataset.

3. (IF-THEN-ELSE Statement and Create a List Report). We have the following small dataset called HealthReport

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Subj Fname Lname Gender Height Weight Date Cal 1024 Alice Smith Female 65 125 12/01/95 2,036 1167 Maryann White Female 68 140 12/02/95 1,800 1168 Thomas Jones Male 190 01/05/96 2,302 1201 Benedictine Arnold Male 68 190 11/30/95 2,432 1302 Felicia Ho Female 63 115 01/01/96 1,972 1344 James Hunter Male 70 188 12/15/95 1,869

Table 3: Health Examination Report

The columns, from left to right, represent the following variables:

Variable Name Descriptions Variable Type Subj Subject number Numeric

Fname First name Character Lname Last name Character Gender Gender Character Height Height (lbs.) Numeric Weight Weight (inches) Numeric Date Date of measurement Numeric Cal Calorie Numeric

Table 4: Descriptions of variables

(a) Read the dataset above into SAS (pay attention to length and format of variables), and change the SAS system settings as follows:

linesize = 64, no current date and time, no page number

(b) Use assignment statement to create a new numeric variable BMI. BMI (Body mass index) is a person’s weight divided by the square of his/her height. In other words, it is defined to be

BM I = W eight

Height2

where the weight unit is kilogram and the height unit is meter. So first you need to convert pound into kilogram and convert inch into meter (1 kilogram = 2.205 pounds, 1 inch = 0.0254 meter), and then calculate BMI.

(c) Use IF-TEHN-ELSE statement to create a new character variable Result. The value of variable Result is determined by the value of BMI according to the following table. Note: the length of the variable Result can be longer than 8. You should specify an appropriate length for variable Result with length statement. The length statement should be placed before the input statement.

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Value of BMI Value of Result Missing ’Missing’

≤ 25 ’Underweight’ > 25 and ≤ 30 ’Normal’

> 30 ’Overweight’

(d) Use SORT procedure to sort the dataset HealthReport first by the variable Gender in an ascending order, and then by the variable Lname in a descending order. The sorted dataset should be saved in another SAS dataset named SrtdHealthReport.

(e) Print the the sorted dataset SrtdHealthReport. When printing the dataset,

1. Use variable Lname and Fname as the identification variables (Use ID statement). 2. Split the dataset into two groups by variable Gender. Calculate the sum of Cal for each

group. 3. Use LABEL statement to assign labels to all variables to make your output more readable.

Particularly, use the descriptions in Table 2 as the labels. You can place the LABEL statement either in the DATA step or in the PRINT procedure. Use labels rather than the variable names when printing the dataset.

4. Add a TITLE (’Health Examination Report Sorted by Last Name’) and FOOTNOTE for this dataset. The content of the FOOTNOTE is: ’BMI = Weight(kg)/(Height(m))^2’.

5. Use the correct FORMAT for variables Date and Cal.

(f) Use Where statement to print the first and last names of female students who are underweight.

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