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Business
Analytics
Jun
2025 Examination
PLEASE NOTE:
This assignment is application based, you have to apply what you have
learnt in this subject into real life scenario. You will find most of the
information through internet search and the remaining from your common sense.
None of the answers appear directly in the textbook chapters but are based on
the content in the chapter
Q1. Given a dataset with missing values, apply
appropriate data treatment techniques to handle the missing data. Justify your
choice of method based on the nature of the dataset. Additionally, analyze a
real-world scenario where missing data impacts decision-making, and implement
suitable imputation methods to improve data quality
|
Student_I D |
Name |
Age |
Gender |
Math_Scor e |
English_Scor e |
Attendance (%) |
|
101 |
Aarav |
20 |
F |
85 |
88 |
95 |
|
102 |
Bhavya |
21 |
M |
78 |
|
88 |
|
103 |
Charan |
22 |
M |
|
82 |
92 |
|
104 |
Deepak |
|
M |
92 |
91 |
|
|
105 |
Esha |
20 |
F |
88 |
85 |
97 |
|
106 |
Farhan |
21 |
|
76 |
79 |
85 |
|
107 |
Gauri |
|
F |
80 |
86 |
90 |
|
108 |
Harshita |
22 |
F |
|
90 |
93 |
|
109 |
Ishan |
23 |
M |
90 |
|
89 |
|
110 |
Jyoti |
20 |
F |
84 |
87 |
|
(10 Marks)
Ans 1.
Introduction
Common across many fields, including business analytics, healthcare,
finance, and education, missing data is a challenge. Missing important information could cause
erroneous analysis, biassed findings, and bad decision-making. In research, predictive modeling, and
strategic planning as well as in data completeness is crucial to guarantee
dependability. Data input mistakes,
system faults, or respondents not giving all the information can all cause
missing values. The kind of the dataset
and the importance of the missing values will determine how missing data are
handled. Good imputation techniques
enable the integrity of the dataset to be restored, therefore guaranteeing
correct analysis and significant discoveries.
We shall go over missing data
Q2A. A pharmaceutical company is testing a new drug
for reducing blood pressure. They conduct a clinical trial with two groups: one
receiving the drug and the other receiving a placebo. The blood pressure levels
are recorded before and after the trial.
1. Analyse the components of a two-sample hypothesis test and
determine why it is appropriate or not for this study. (1 Mark)
2. Given that the obtained p-value is 0.08, break down the
decision-making process for rejecting or failing to reject the null hypothesis
at a 5% significance level. (1 Mark)
3. Examine the potential risks associated with Type I and Type
II errors in this study and discuss how they could affect the interpretation of
results. (1 Mark)
4. The company wants to check whether the drug's effectiveness
varies across different age groups (e.g., 30-40, 41-50, 51-60). Analyse whether
the Chi- square test of independence is an appropriate test in this scenario.
(1 Mark)
5. Differentiate between the Chi-square Goodness of Fit test and
the Chi-square test of independence, and analyse how each applies to different
types of pharmaceutical studies. (1 Mark) (5 Marks)
Ans 2A.
Introduction
Clinical
trials are essential for evaluating the effectiveness of new drugs. A
pharmaceutical company is testing a drug for reducing blood pressure, comparing
it with a placebo. Statistical analysis, including hypothesis testing, helps
determine if the drug has a significant effect. This study examines hypothesis
testing, decision-making based on p-values, error risks, and
Q2B. A company wants to predict sales based on
advertising expenses using a simple linear regression model. The dataset for 5
months is given below:
|
Month |
Advertising Expense (X in Rs 1000s) |
Actual Sales (Y in Rs 1000s) |
Predicted Sales ( in Rs 1000s) |
|
1 |
2 |
4 |
3.8 |
|
2 |
3 |
5 |
5.2 |
|
3 |
5 |
7 |
6.9 |
|
4 |
7 |
10 |
9.5 |
|
5 |
9 |
12 |
11.7 |
1. Formulate the simple linear regression equation based on the
given data.
2. Determine the regression coefficients (: Intercept : Slope)
and interpret their impact on sales.
3. Derive insights from the regression equation, understanding
the baseline performance and the impact of advertising expenses on sales.
4. Suggest recommendations based on findings, highlighting the
effectiveness of advertising expenses.
Instructions:
- Use Excel to compute the regression equation, coefficients,
and R² value.
- Paste the Excel output with formulas to demonstrate
calculations.
- Insights should be based on data from Excel analysis (5
Marks)
Ans
2B.
Introduction
Advertising plays a crucial role
in driving sales, and companies use predictive models to understand its impact.
A simple linear regression model helps determine the relationship between
advertising expenses and actual sales. Using a dataset covering five months,
this analysis formulates the regression equation, determines regression
coefficients, interprets their impact, and provides insights on
Dear students, get fully solved assignments by
professionals
Do send your query at :
or call us at : 08263069601
(Plagiarism proofed assignments available with 100% surety and refund)
