Question 1

When using PROC MEANS to summarize data, a programmer needs to display only the variables "Time", "Distance", and "Speed" from a dataset, while also calculating the mean and standard deviation for those variables. Which of the following VAR statements is the most efficient way to achieve this while maintaining the original order in the dataset?

Options :

A : `proc means data=work.RunData mean std; var Time Distance Speed; run;`

B : `proc means data=work.RunData mean std; var Speed Distance Time; run;`

C : `proc means data=work.RunData; var Time Speed; run;`

D : `proc means data=work.RunData; run;`

Answer: A

Question 2

When performing a data manipulation task using the simple action set in SAS Viya, you need to group the data by the 'region' variable and then calculate the total sales for each region. Which action should you use to accomplish this task within the simple action set?

Options :

A : simple.groupby

B : aggregation.groupby

C : simple.summary

D : simple.aggregate

Answer: D

Question 3

Consider the following SAS code which intends to retrieve values from an array to calculate the average sales for the first quarter: `

data work.quarterly_sales;

array qtr_sales[3];

do i=1 to 3;

set sales_data(keep=jan feb mar);

qtr_sales[i] = sales_data{i};

end;

avg_sales = mean(of qtr_sales[*]);

run;

The dataset `sales_data` has three variables named `jan`, `feb`, and `mar`, containing the sales for each month of the first quarter. Which statement is true regarding this code?

Options :

A : The code will correctly calculate `avg_sales` as the average of the first quarter sales.

B : The `set` statement is incorrectly placed inside the loop, causing an error.

C : The mean function is not used correctly and will result in an error.

D : The array subscript cannot use `sales_data{i}`, it should be `qtr_sales[i] = sales_data[i];`.

Answer: B

Question 4

A programmer wants to utilize the `TABULATE` procedure in SAS Viya for generating a summary report. They need to limit the output to only include the observations for which the 'type' variable equals 'Residential'. Which option demonstrates the correct use of the `WHERE=` parameter in PROC TABULATE to accomplish this task?

Options :

A : `PROC TABULATE DATA=real_estate; WHERE= type = 'Residential'; CLASS property_type; VAR price; TABLE property_type, price*SUM; RUN;`

B : `PROC TABULATE DATA=real_estate TABULATE=WHERE(type = 'Residential'); CLASS property_type; VAR price; TABLE property_type, price*SUM; RUN;`

C : `PROC TABULATE DATA=real_estate; TABLE property_type, price*SUM / WHERE(Type = 'Residential'); CLASS property_type; VAR price; RUN;`

D : `PROC TABULATE DATA=real_estate(table=WHERE(type = 'Residential')); CLASS property_type; VAR price; TABLE property_type, price*SUM; RUN;`

Answer: A

Question 5

Assume that you are working with a large dataset in CAS, and you have a need to create a flag variable that indicates whether certain criteria are met. This flag is based on a calculation that you do not want to repeat in multiple places throughout your DATA step code. How can the `computedVarsProgram=` parameter be utilized to optimize performance and maintainability?

Options :

A : Use the `computedVarsProgram=` parameter to define the flag calculation and reference the flag variable later in the DATA step without redefining the calculation.

B : Set the `computedVarsProgram=` parameter to create a macro variable with the desired flag value so it can be used throughout the DATA step.

C : Apply the `computedVarsProgram=` parameter in multiple DATA steps so each one can perform the flag calculation independently.

D : Invoke the `computedVarsProgram=` parameter at the end of the DATA step to store the results of the flag calculation for subsequent steps.

Answer: A

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