MIB IIBM CASE STUDY ANSWER SHEETS – When variance between predicted and actual values is not same, it is called – a. Multicolinearity b. Heteroskedasticity c. Homoscadesticity d. Autocorrelation
MIB IIBM CASE STUDY ANSWER SHEETS – When variance between predicted and actual values is not same, it is called – a. Multicolinearity b. Heteroskedasticity c. Homoscadesticity d. Autocorrelation
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Business Analytics Using SAS
Multiple choice:
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Which one of the following is the value of the variable data work? One; a = 2; b = 3; c = a ** b; run;
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6
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8
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9
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None of the above
II. Which one of the following statement can’t be part of “PROC FREQ” (1)
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Output
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Weight
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Set
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Tables
III. Which one is not a data type in SAS.
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Numeric
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Date
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Character
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Boolean
IV. Which of the following statements are used to read delimited raw data file and create an SAS data set (1)
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Data, Infile, Input
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Data, Set, Input
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Data, Set, Infile
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Data & Set
V.Which of these is casual model technique
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Moving average
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Exponential Smoothing
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Regression
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Trend Model
VI. When variance between predicted and actual values is not same, it is called –
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Multicolinearity
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Heteroskedasticity
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Homoscadesticity
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Autocorrelation
VII. Is there a limitation of records in SAS? (1)
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No
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Ye
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Can’t say
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None of the above
IX. what is syntax used for assigning library in SAS (1)
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LibSet
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LibData
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Data
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Libname
VIII. Which one is not a window in SAS (1)
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Editor
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Log
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drive
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results
X. What is the syntax to print results in SAS (1)
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Proc set
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Proc print var
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Proc Print
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Proc Sql
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variance between predicted
Part Two
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Write data step to assign work dataset, say ABC with limitation of 10 observations only? (5)
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Write the role of PDV in SAS (5)
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Explain lib name function with read-only access (5)
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What is the starting date in SAS, how does SAS reads any given date (5)
variance between predicted
Section B: Caselets (40 marks)
Caselet 1
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Answer the question based on data given below. Name of the dataset is class–
Roll Number |
Class |
Age |
Gender |
Subject |
Sports |
||||
|
|
|
|
|
|
|
|
|
|
001 |
1 |
10 |
M |
Maths |
Cricket |
||||||
002 |
1 |
11 |
M |
English |
Tennis |
||||||
003 |
2 |
9 |
F |
Maths |
Football |
||||||
004 |
4 |
7 |
F |
Science |
Football |
||||||
005 |
3 |
7 |
M |
Maths |
Cricket |
||||||
006 |
5 |
10 |
F |
Science |
Tennis |
||||||
007 |
3 |
7 |
F |
Art |
Cricket |
||||||
|
|
|
|
|
|
|
|
|
|
|
|
variance between predicted
Questions
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Write code to see frequency distribution by Gender & Subject? (10)
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Write code to filter student age less than 10 and like football and Maths? (10)
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Write code to sort the data by age? (10)
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Which sport has the maximum demand, write code to see proportionate (10)
Section C: Applied Theory (30 marks)
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Explain how SAS can replace excel, talk about 3 key features of SAS? (15)
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What is the meaning of debugging in SAS, how can it help in code writing?
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