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.