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SASInstitute SAS Certified Associate: Programming Fundamentals Using SAS 9.4 Sample Questions (Q188-Q193):

NEW QUESTION # 188
The data set SASHELP. CARS contains information on different vehicles. How do you correctly write the observations with Type of 'SUV' to the suv data set and Type of 'Sedan' to the sedans data set?

A. data SUV;
data Sedans;
set sashelp.cars;
if Type = SUV then output SUV;
else if Type = Sedan then output Sedans;
run;
B. data SUV Sedans;
set sashelp.cars;
if Type = 'SUV' then output SUV;
else if Type = 'Sedan' then output Sedans;
run;
C. data=SUV data=Sedans;
set sashelp.cars;
if Type = 'SUV' then output SUV;
else if Type = 'Sedan' then output Sedans;
run;
D. data= (SUV Sedans) ;
set sashelp.cars;
if Type = 'SUV' then output SUV;
else if Type = 'Sedan' then output Sedans;
run;

Answer: B

Explanation:
The correct syntax for creating two separate data sets based on a condition in SAS involves using a single DATA step with multiple data set names followed by a SET statement and conditional OUTPUT statements.
Here's a breakdown of why option B is the correct answer:
data SUV Sedans;
set sashelp.cars;
if Type = 'SUV' then output SUV;
else if Type = 'Sedan' then output Sedans;
run;
* This option correctly uses a single DATA step to declare two data sets (SUV and Sedans). It reads from the sashelp.cars data set and uses conditional statements to output observations to the respective data sets based on the value of the Type variable. The output statement is used to explicitly direct observations to the specified data set.
* Option A: The syntax data=SUV data=Sedans; is incorrect. The correct syntax to create multiple data sets in a DATA step does not include equal signs (=).
* Option C: The syntax within the conditional statements is incorrect (if Type = SUV and if Type = Sedan). The values for Type should be enclosed in quotes to specify that they are strings.
* Option D: The syntax data= (SUV Sedans) ; is incorrect. The correct method to declare multiple data sets in a DATA step does not use parentheses or an equal sign.
References:The correctness of option B is based on standard SAS programming practices for conditional data manipulation within a DATA step. This approach is commonly documented in SAS programming resources such as the SAS 9.4 documentation and various SAS programming guides. The use of the output statement for directing data to specific datasets based on conditions is a fundamental technique in efficient data handling in SAS.

NEW QUESTION # 189
You have three datasets: 'CUSTOMER INFO', 'ORDER DETAILS', and 'PRODUCT_DATA', each containing a unique 'CUSTOMER ID', 'ORDER ID', and 'PRODUCT ID' respectively. You need to create a new dataset 'COMPLETE DATA' that combines the data from all three datasets based on the following logic: 1. Merge 'CUSTOMER INFO' and 'ORDER DETAILS' datasets on 'CUSTOMER ID'. 2. Then, merge the resulting dataset with 'PRODUCT DATA' on 'ORDER ID'. Write the SAS code to achieve this using MERGE statements.

Answer: D,E

Explanation:
Both options B and E correctly merge the datasets in the specified order, creating the desired 'COMPLETE_DATA' dataset. Option B first merges 'CUSTOMER_INFO' and 'ORDER_DETAILS' on 'CUSTOMER_ID', storing the result in a temporary dataset 'TEMP'. Then, it merges 'TEMP' with 'PRODUCT_DATA' on 'ORDER_ID' to create 'COMPLETE_DATA'. Option E achieves the same result by first merging 'ORDER DETAILS' and 'PRODUCT_DATA' on 'ORDER_ID' and then merging the resulting 'TEMP' dataset with 'CUSTOMER_INFO' on 'CUSTOMER_ID'. Option A incorrectly merges all three datasets at once using 'CUSTOMER_ID', which would not produce the intended result. Option C also attempts to merge all three datasets at once, but it incorrectly uses 'ORDER_ID' for merging all datasets. Option D attempts to merge 'CUSTOMER_INFO' and 'ORDER_DETAILS', then tries to merge the 'COMPLETE_DATA' with 'PRODUCT_DATA' without defining 'COMPLETE_DATA' properly, leading to errors.

NEW QUESTION # 190
You have a dataset with a variable named 'SALES AMOUNT representing the sales value. You want to create a new variable 'SALES CATEGORY' that categorizes sales into 'Low', 'Medium', and 'High' based on the following criteria: Low: SALES AMOUNT < 1000 Medium: 1000 <= SALES AMOUNT < 5000 High: SALES AMOUNT >= 5000 Which of the following DATA step code segments will correctly accomplish this task?

Answer: E

Explanation:
Option B is the only correct code segment. The IF-THEN-ELSE statements are correctly structured to cover all possible scenarios of the sales amount. Option A has incorrect logic for the 'Medium' category as it only checks if SALES AMOUNT is less than 5000, not also greater than or equal to 1000. Option C is incorrect because 'elseif is not a valid keyword in SAS, it should be 'else if. Option D has redundant 'else if statements and is not efficient. Option E has the same problem as option C with the use of 'elseif instead of 'else if. Therefore, only Option B correctly categorizes sales based on the provided criteria.

NEW QUESTION # 191
Which iterative DO statement is invalid?

A. Do reverse = 10 to 1 by -1;
B. Do year = 2000 to 2016 by 2;
C. Do 100 to 1200 by 100;
D. Do num = 1.1 to 1.9 by 0.1;

Answer: C

NEW QUESTION # 192
Which PROC PRINT statement controls the order of the variables displayed in the report?

A. VAR
B. SELECT
C. DROP
D. KEEP

Answer: A

Explanation:
In PROC PRINT, the VAR statement is used to control the order of the variables displayed in the report. You can list the variables in the order you want them to appear. The KEEP statement can control which variables appear, but not their order. DROP and SELECT are not valid statements within PROC PRINT for controlling the order of variables.
References
* SAS documentation for PROC PRINT.

NEW QUESTION # 193
......

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