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.

In the provided image of the SAS code for the PROC PRINT step, the following statements are present:

• proc print data=sashelp.cars; - PROC PRINT step beginning
• var Make Model MSRP MPG_City MPG_Highway Horsepower Weight; - VAR statement to specify variables to print
• format Weight comma8.; - FORMAT statement to apply a format to a variable
• The final run; statement which would be necessary to execute the PROC PRINT step is not visible in the image, but it can be inferred to be there since every PROC step must be ended with a run; or quit; statement.

Thus, there are four statements related to the PROC PRINT step.

References:

• SAS 9.4 Language Reference: Concepts, "PROC PRINT"
• SAS documentation on "VAR Statement" and "FORMAT Statement"

In a DATA step concatenation in SAS, when multiple datasets are listed in a SET statement, SAS concatenates the datasets vertically, stacking them one on top of the other. The length of variables in the resulting dataset is determined by the first dataset that appears in the SET statement. If the same variable appears in multiple datasets, SAS uses the length as it is first encountered. It does not require columns with the same name to be renamed; rather, it stacks them directly. There is no maximum number of tables that can be listed in a SET statement for concatenation; more than two can be concatenated. Lastly, concatenation combines data vertically, not horizontally as option D suggests.

References

• SAS 9.4 Language Reference: Concepts, "Concatenating Data Sets."

The FORCAST dataset is created from the INVEST dataset, which has 10 observations as seen in the PROC PRINT report. For each observation in INVEST, three new observations are added in FORCAST, one for each year's balance calculation (year=1, year=2, year=3). This is achieved by the output; statement after each balance calculation, which writes the current state of the data step to a new row in the dataset. Therefore, since there are 10 original observations, and each leads to three new observations, the total number of observations in the FORCAST dataset will be 30 (10 observations from INVEST multiplied by 3 years each).

References:

• SAS documentation on the DATA step and output statement, SAS Institute.

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.

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.

In SAS, the FORMAT procedure (PROC FORMAT) allows users to create custom formats that can be used to change the way data is displayed without altering the data itself. The VALUE statement within PROC FORMAT is a key component of this procedure.

The VALUE statement can indeed create both numeric and character formats, which is why option C is correct. Numeric format names typically do not start with a $ sign (this is reserved for character format names), and the keyword UNKNOWN is not a part of the VALUE statement syntax; it is used in a different context within PROC FORMAT, specifically for handling undefined data values when using custom formats.

Moreover, the LIB= option is not used within the VALUE statement. The LIB= option is used at the PROC FORMAT level to specify the library where the formats should be stored or from which they should be read.

References

• SAS 9.4 documentation for the PROC FORMAT and VALUE statement.
• "SAS Formats and Informats." in "Step-by-Step Programming with Base SAS 9.4" from the SAS Institute.

In SAS, the DATA step is a powerful tool that allows programmers to perform a variety of tasks such as reporting, managing, and analyzing data. The DATA step processes data one observation at a time, making it highly efficient for data manipulation tasks. It enables the creation of new datasets, modification of existing ones, and complex data transformations. Additionally, within a DATA step, you can use a wide range of programming statements and functions to calculate new variables, merge or sort datasets, and perform conditional processing. The flexibility and functionality provided by DATA steps make them a fundamental part of SAS programming for handling and preparing data for further analysis or reporting.References: SAS 9.4 Language Reference: Concepts.

In SAS, when you use a BY statement in a DATA step, SAS creates two temporary variables for each variable listed in the BY statement: one to indicate the first occurrence (FIRST.variable) and another to indicate the last occurrence (LAST.variable) of the value within the BY-group. Given the provided code and assuming that State is the variable used in the BY statement, SAS will create First.State and Last.State. Thus, option A is correct.

References:

• SAS documentation on the BY statement, SAS Institute.

In SAS, the code you provided involves creating two datasets, table1 and table2, from the dataset sashelp.shoes. The key part to understand here is how the DATA statement and OUTPUT statement interact with the specified datasets.

• DATA Statement: The statement data table1 table2; initiates the creation of two new datasets named table1 and table2.
• SET Statement: The set sashelp.shoes; statement is used to read data from the sashelp.shoes dataset. This dataset includes data on shoe sales from SASHELP library, which is commonly used for demonstration purposes in SAS.
• OUTPUT Statement: In the context of the DATA step where multiple datasets are specified in the DATA statement (as in table1 table2), the OUTPUT statement without a dataset name specified outputs the current observation to all datasets listed in the DATA statement. This is a critical point because it determines where the data goes after processing in the DATA step.
• Execution: When the run; statement is executed, it processes each observation from sashelp.shoes. For each observation, because there is no condition or additional OUTPUT statements specifying dataset names, each observation is output to both table1 and table2.

Therefore, the correct behavior as described is that each observation in sashelp.shoes is written to both table1 and table2. This effectively duplicates each row from the source into both target datasets.

References:

• SAS 9.4 Language Reference: Concepts, "DATA Step Processing" and "OUTPUT Statement" sections provide detailed explanations on how DATA steps process and how OUTPUT statement works in different contexts.
• Practical examples and explanations from SAS programming courses and official SAS documentation, which discuss DATA and SET statements, and their interaction with OUTPUT in data duplication scenarios.

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 answer is option D, which uses the LIBNAME statement correctly to assign a library reference to an Excel workbook and specifies the correct syntax for accessing a worksheet within that workbook. The syntax for this option is:

libname exlib xlsx "c:\class.xlsx";

proc print data=exlib.class_test;

run;

This code snippet assigns the library reference exlib to the Excel workbook located at c:\class.xlsx using the XLSX engine. The PROC PRINT step is then used to display the contents of the worksheet named CLASS_TEST within that workbook. The library reference exlib combined with the dataset name class_test (following the .) correctly specifies the worksheet to be printed. The other options (A, B, C) are incorrect due to various reasons: incorrect syntax for the LIBNAME statement, incorrect specification of the dataset to be printed, and incorrect path specifications.References: SAS 9.4 Guide to Software Updates.

The PROC SORT statement that specifies the sort variable is: BY

The BY statement in PROC SORT is used to specify the variable(s) by which the data should be sorted.

The DROP statement during the compilation phase of the DATA step flags variables in the Program Data Vector (PDV) to be dropped when the data set is output. This means that although the variables exist in the PDV during the DATA step execution, they will not be written to the output data set. The DROP statement does not affect the order of variables (which is the purpose of the ORDER= data set option), nor does it remove variables from the input data set or prevent them from being created in the PDV.

References:

• SAS documentation on the DROP statement.

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

The default length of numeric variables in SAS data sets is 8 bytes.

In SAS, the default byte size of a numeric variable is 8 bytes. This allows for a significant amount of precision and a wide range of numeric values to be stored within a numeric variable, regardless of the actual number of digits in the number being stored.

References:

• SAS documentation on numeric variables, SAS Institute.

The correct answer is B. The set statement in SAS can concatenate multiple datasets together. The AMERICAN and NATIONAL datasets appear to have the same structure and variables, so the set statement without any options will combine them into one dataset called BASEBALL. The order of the datasets in the set statement determines the order of the observations in the output dataset, and since there is no variable that needs renaming to match between the two datasets, option B is the correct answer.

References:

• SAS documentation on the set statement.

The PROC PRINT statement is used for printing SAS datasets. To customize the column headers in the report, you use the label statement within the PROC PRINT procedure to assign new labels to variables, and the label option in the PROC PRINT to activate these labels. The noobs option suppresses the printing of observation numbers in the report.

Option B has the correct syntax for what is being requested:

• proc print data=cities label noobs; specifies the dataset to print with the label option to display variable labels and noobs to hide the observation numbers.
• label Name='Employee Name' City='Birth City'; assigns the label 'Employee Name' to the 'Name' variable and 'Birth City' to the 'City' variable.
• run; signifies the end of the PROC PRINT procedure.

Options A, C, and D are incorrect due to syntax errors:

• A uses an incorrect option showlabelse instead of label and noobs.
• C is incorrect because it lacks the label option in the proc print statement which is necessary to actually display the labels, and the labels are being incorrectly used within the proc print instead of in a label statement.
• D has several issues: there is no display statement in SAS, the option noobs should be outside of the proc print statement, and the labels should be defined in a label statement, not within proc print.

References:

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

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.