A00-215 Sample Questions Answers

In SAS, the correct syntax for assigning labels to variables is to use the LABEL statement within a DATA step or a PROC step. Labels are assigned to variables using the format variable='label'. The correct syntax for the LABEL statement is represented by option B.

Here’s the breakdown:

• FName=’First Name’ correctly assigns the label First Name to the variable FName.
• LName=’Last Name’ correctly assigns the label Last Name to the variable LName.
• Each variable and label pair is separated by a space, and the overall statement ends with a semicolon, which is the proper syntax for a LABEL statement in SAS.

Options A, C, and D are incorrect due to various syntax errors like the use of the wrong character for the apostrophe, missing apostrophes, incorrect punctuation, and in the case of option C, an incorrect conjunction ‘and’ which is not used in LABEL statements.

References:

• SAS 9.4 documentation for the LABEL statement: SAS Help Center: LABEL Statement

The correct answer is A. The SET statement in SAS is used within a DATA step to specify which existing SAS dataset is to be read. This statement is used to read in data from an existing SAS dataset to be processed in the current DATA step. The SET statement does not specify an output data set; that is determined by the name specified in the DATA statement.

Options B, C, and D are incorrect because:

• B and C are incorrect as the SET statement is not used in the PROC SORT step at all.
• D is incorrect because the SET statement specifies the input dataset, not the output dataset, in the DATA step.

References:

• SAS 9.4 Language Reference: Concepts, "DATA Step Processing"
• SAS documentation on the SET statement.

When creating two SAS data sets with a DATA step, you should name both data sets in the DATA statement. This tells SAS to create two separate data sets from the same DATA step. Using an OUT= option in the WHERE statement or a PUT statement are not correct methods for creating data sets. A SET statement is used to read data into the DATA step, not to create output data sets.

References:

• SAS documentation on the DATA step for creating multiple data sets.

The type of error that does not produce expected results and does not generate errors or warnings in the log is a logic error. Logic errors occur when there is a flaw in the program's logic, which causes it to operate incorrectly, but the syntax is correct so it does not produce any error or warning messages. Unlike syntax errors which are mistakes in the program's code that prevent it from compiling or running, logic errors are more insidious because the program still runs but yields incorrect results. For example, a programmer may accidentally code an incorrect formula or use a wrong variable name that still exists, so the program runs but produces incorrect output.

References:

• SAS documentation on error types.

The report shown is a cross-tabulation of 'Region' by 'Product'. The FREQ Procedure indicates that PROC FREQ has been used, and the presence of 'Frequency', 'Percent', 'Row Percent', and 'Column Percent' suggests that a cross tabulation (or contingency table) has been requested. The correct code for this output would include the tables statement to specify the two variables ('Region' and 'Product') with an asterisk between them, which indicates a request for a cross-tabulation of these two categorical variables, and the crosslist option to display the table in a cross-tabulated list format. Therefore, option D is the correct answer:

proc freq data=sashelp.shoes;

tables region*product / crosslist;

run;

Options A and C use the order=freq option incorrectly, as this option would order the table by frequency counts rather than providing a cross-tabulation. Option B is missing the crosslist option needed to produce the cross-tabulated format.

The correct syntax for a conditional if-then block in SAS that includes a do group for executing multiple statements is:

if condition then do;

statement1;

statement2;

end;

In Option B, the syntax if age<13 then do; opens a do group, and age_Cat='Pre-teen'; and account='No Social Media'; are the two statements inside the do group, followed by an end; statement to close the group. However, there is a typo with the use of dashes instead of equal signs for assignment in the variable statements which seems to be an error, so technically, none of the provided options has the correct syntax without an error. The correct syntax should use equal signs (=) for assignment within the do group:

if age<13 then do;

age_Cat='Pre-teen';

account='No Social Media Allowed';

end;

References:

• SAS documentation on conditional processing with IF-THEN/ELSE statements, SAS Institute.

The PROC MEANS statement is used to compute descriptive statistics of data in SAS. Option A is the correct code to produce the report shown in the first image because of the following reasons:

• data=sashelp.shoes specifies the dataset on which the procedure is to be performed.
• sum mean specifies that the summary statistics should include the sum and mean of the variables.
• var Sales; specifies that the variable Sales is the analysis variable for which the summary statistics are to be computed.
• class Product; specifies that the procedure should classify results by unique values of the Product variable. This will produce separate statistics for each type of product, which aligns with the structure of the report provided in the image.

Options B, C, and D are incorrect for the following reasons:

• B uses group instead of class, and group is not a valid statement in the context of PROC MEANS. Also, var Sale; is incorrect as the variable name is Sales.
• C includes nobe; which is not a valid SAS option and seems to be a typo. The by statement is used for sorting data, not for classifying groups as class does.
• D incorrectly uses sum Salad; and mean Sales; as separate statements and has an invalid use of by product; which is not needed here.

References:

• SAS 9.4 documentation for the PROC MEANS statement: SAS Help Center: PROC MEANS

In SAS, the SUBSTR function is used to extract a substring from a character string. The function syntax is SUBSTR(string, position, length), where:

• string is the variable or string literal you want to extract the substring from.
• position is the starting position of the substring within string.
• position starts counting at 1 in SAS, not 0 as in some other languages.
• length is the number of characters to extract.

For the value of date provided ("02Apr2019"), we want to extract the year, which is the four characters at the end of the string.

Here's how each option would work given the string:

A) year=substr(date, 7, 4);This starts at the 7th character of the string ("2019") and extracts 4 characters, which correctly represents the year.

B) year=substr(date, 4, 6);This starts at the 4th character ("Apr2019") and would extract 6 characters, which gives us "Apr201", not just the year.

C) year=substr(date, 6, 4);This starts at the 6th character ("r2019") and would extract 4 characters, resulting in "r201", which is not correct.

D) year=substr(date, 4, 7);This starts at the 4th character and would extract 7 characters, resulting in "Apr2019", which is the whole string from the 4th character to the end, not just the year.

The correct answer is A, as it extracts the four-digit year from the end of the string.

References:

• The SAS documentation on the SUBSTR function, which details how to use it for extracting parts of strings.
• SAS programming tutorials that often provide examples of common functions like SUBSTR for string manipulation

The PROC MEANS report shown in the image displays statistics for a single variable Age with no decimal places. The correct SAS code to generate such a report is option D, which uses the PROC MEANS procedure with the maxdec=0 option to control the number of decimal places displayed (in this case, zero) and specifies Age as the analysis variable using the var statement.

The PROC MEANS procedure computes descriptive statistics for numeric variables. The maxdec=0 option is used here to remove decimal places from the report output, which matches the output shown where the mean, standard deviation, minimum, and maximum are all integers.

The other options are incorrect for the following reasons:

• A uses the class statement, which is not appropriate here because Age is not a classification variable but an analysis variable.
• B uses the group statement, which is not a valid statement in the PROC MEANS procedure.
• C uses the by statement, which requires the data to be sorted by the BY variable and does not fit the output provided since it would produce separate statistics for each value of Age.

References:

• SAS 9.4 documentation for the PROC MEANS statement: SAS Help Center: PROC MEANS

The step that reads the SASHELP.BASEBALL data set and creates the temporary data set CATCHERS is:

data catchers;

set sashelp.baseball;

where position='C';

run;

This DATA step creates a new data set named catchers by reading in data from sashelp.baseball and selecting only those observations where the variable position has the value 'C', which stands for catchers.

To subset data in SAS using the data step, the where statement is used to specify the conditions that observations must meet to be included in the new data set. The correct syntax for subsetting the SASHELP.BASEBALL data set to include only players in the 'East' Division with 75 or more hits is as follows:

data bball;

set sashelp.baseball;

where Division = 'East' and nHits >= 75;

run;

This code, as shown in option D, uses the where statement with the correct logical operator and to ensure that both conditions must be true for a record to be included in the new dataset. Options A, B, and C either use incorrect syntax or logical operations that do not match the required conditions for the subset. Option A has an incorrect combination of conditions, B uses two where statements which is not valid syntax, and C incorrectly uses the or operator which would include players not in the 'East' Division or with fewer than 75 hits.

The FORMAT statement in the DATA step assigns formats to variables for the SAS dataset being created. In the code provided, MSRP is given the dollar12. format and Invoice is given the dollar10. format. However, during the PROC PRINT step, MSRP is reassigned to the comma12.2 format. The format specified in the most recent PROC step or DATA step that executes is the one that is used in the output.

Therefore, the format for MSRP in the PROC PRINT output will be comma12.2, making the answer: B. Comma12.2

References:

• SAS documentation on PROC PRINT and FORMAT statement, SAS Institute.

Option B is the correct answer. This code will create two datasets as described. The keep= option in the data chips statement will ensure that only QtySold, Price, and Product are kept in the chips dataset, and because othersnacks does not have a keep= option, it will contain all the variables from the input dataset. The if-then-else logic directs the observations to the correct dataset based on the Type value.

Option A incorrectly uses a keep statement within the if block, which is not valid syntax. Option C attempts to use a keep statement after the output statement, which will not correctly subset the variables for the chips data set. Option D incorrectly applies the keep= option to the set statement, which would affect both output data sets, not just chips.

References:

• SAS documentation on the output statement.
• SAS documentation on subsetting data in the DATA step.

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.

The correct syntax for generating the mean and standard deviation for specified variables using PROC MEANS is shown in option A. The PROC MEANS statement specifies the dataset to analyze (data=class) and includes the options (mean std) directly in the PROC statement. The VAR statement then lists the variables for which the statistics should be calculated (Height and Weight). The other options listed in B, C, and D are not correct syntax for PROC MEANS.

SAS handles missing values distinctively based on the data type of the variable. For numeric variables, SAS represents missing values with a period (.). For character variables, missing values are represented by a blank space. This handling is crucial for distinguishing between actual data entries and absent data, particularly in statistical calculations and data processing. Options B, C, and D incorrectly describe the representation of missing values in SAS, which does not use special characters like 'N', 'C', or '$' for this purpose.

References:SAS documentation on handling missing data, SAS Institute.

To create SAS date values, the correct syntax involves specifying the date in a string format followed by the letter 'd'. This indicates to SAS that the string should be interpreted as a date value. Therefore, the correct answers are:

• A. "10/19/2019"d - This format directly specifies the month, day, and year, enclosed in quotes followed by 'd', which SAS correctly interprets as a date value.
• C. "19Oct2019"d - This format uses a three-letter abbreviation for the month combined with the day and year, also followed by 'd'. This is another valid way to specify a date in SAS.

Option B, mdy(10, 19, 2019), is incorrect because while the MDY function does create date values from month, day, and year components, the function itself should be used within a DATA step or another context where SAS functions are evaluated, and it doesn't directly create a date literal in the same way as options A and C.

Option D, mdy(19, Oct, 2019), is syntactically incorrect because the MDY function expects numeric arguments for the month, day, and year, and "Oct" as a literal month name is not a valid numeric argument.

References: SAS 9.4 Language Reference: Concepts.

The correct answer is B. The DATA step in SAS is used to read, process, and create data sets. It can read from various sources, not just raw data files but also existing SAS datasets and external databases. It processes the data by executing operations on each observation and can create one or more SAS datasets as output. The other options are incorrect because:

• A is incorrect because the DATA step is not limited to reading only raw data files.
• C is incorrect because the DATA step can output multiple data sets using the OUTPUT statement.
• D is incorrect because the DATA step does not have to be the first step in a program; it can be used anywhere in the program where data processing is required.

References:

• SAS 9.4 Language Reference: Concepts, "DATA Step"
• SAS documentation on processing data with the DATA step.

The VAR statement in PROC MEANS is used to specify the variables for which you want to calculate the descriptive statistics such as the mean and standard deviation. You list the names of one or more numeric variables after the VAR statement to include them in the analysis. Therefore, option D is the correct answer.

References

• SAS documentation for PROC MEANS.

In the given statement, BirthDate = 15DEC2005’d;, the 'd' denotes a SAS date constant, which is a numeric value representing a specific date. SAS date values are stored as numeric variables counting the number of days from January 1, 1960. Therefore, BirthDate is a numeric variable, making option B correct. This constant does not represent a character string (eliminating A), and the byte size of any numeric variable in SAS is 8 by default, not 9 (eliminating C). There is no syntax error in the statement (eliminating D).

References:

• SAS documentation on dates, times, and datetime values, SAS Institute.