The INPUT function is used to convert a character string to a numeric value using a specified informat. The ‘date9.’ informat correctly reads the ‘DDMMMYYYY’ pattern (e.g., 01JAN2023). The PUT function (option B) converts a value to character. The ‘ddmmyyyy10.’ informat (option C) expects a different format with slashes or dashes. Simple multiplication (option D) does not perform date conversion.

SAS issues a ‘multiple lengths’ note when a variable with the same name exists in two or more input datasets but is defined with different lengths. The length is determined by the first dataset in which the variable is encountered during compilation. To avoid truncation, explicitly define the variable’s length with a LENGTH statement at the start of the DATA step before any reference to the variable in a SET, MERGE, or assignment statement.

For the first observation, the variable Bonus does not exist in the input dataset and is not initialized before the IF statement. If Sales<=50000, the IF condition is false, so the assignment 'Bonus=1000' never executes. SAS then tries to execute 'Bonus = Bonus + 500'. Since Bonus is missing (.) in this first calculation, 'missing + 500' results in a missing value. All subsequent observations will retain the value from the previous iteration due to automatic retention in the DATA step, leading to unpredictable results, highlighting the importance of variable initialization.

In PROC PRINT, the WHERE statement is used to subset observations for processing. Option A uses the correct WHERE statement and VAR statement to select columns. Option B incorrectly uses an IF statement, which is not valid in most PROCs. Option C uses dataset options correctly but uses ‘columns’ instead of the standard ‘var’. Option D uses a non-existent ‘subset’ statement.

While options C (SELECT) and D (IFN function) are also valid, the nested IF-THEN/ELSE statement in option A is the most standard, readable, and efficient for this classic range assignment. It evaluates conditions in order and stops at the first true condition. Option B uses multiple independent IF statements, which is inefficient and could lead to incorrect results if Score is, for example, 95 (it would first set Grade=’A’, but the subsequent IF for Score<70 would then incorrectly reset it to 'F').

NODUPKEY removes observations where values of all BY variables are identical. NODUPRECS (or its alias NODUP) removes observations where values of all variables in the dataset are identical. To achieve both types of deduplication, you can use both options: `proc sort data=myData nodupkey noduprecs;`. Option B is a manual and complex alternative. Option C is incorrect. Option D is a valid alternative method but not the asked-for correction to the PROC SORT approach.

This describes the default behavior called FLOWOVER. When using list input (e.g., `input name $ age weight;`) and SAS reaches the end of a data line before all variables are read, it by default moves to the next line to continue reading for the current observation. This is often undesirable. The MISSOVER, TRUNCOVER, or STOPOVER options in the INFILE statement are used to control this behavior and assign missing values instead.

You cannot use a WHERE statement in PROC FREQ to filter based on the computed frequency. The correct approach is to use the OUT= option in the TABLES statement to create a dataset containing the frequencies (variables: Department, COUNT, PERCENT). Then, use a subsequent DATA step to subset this much smaller dataset where COUNT > 50, and finally print it. Option A and B incorrectly try to use WHERE on the statistic. Option C creates the full report without filtering.

This is a SUM statement. Its key features are: 1) The variable on the left (Total) is automatically retained. 2) It is initialized to 0 at the beginning of the DATA step execution. 3) Missing values in the expression on the right (Amount) are treated as 0. This is different from the assignment statement `Total = Total + Amount;` (option C), which would require explicit retention and initialization to avoid missing values in the first iteration.

The INPUT function is used to convert a character string to a numeric value using a specified informat. The ‘date9.’ informat correctly reads the ‘DDMMMYYYY’ pattern (e.g., 01JAN2023). The PUT function (option B) converts a value to character. The ‘ddmmyyyy10.’ informat (option C) expects a different format with slashes or dashes. Simple multiplication (option D) does not perform date conversion.0