1. Which variables would you chose as dependent and independent variable – why?
a. Interpret the regression result and comment on R and F statistic
b. Explain the equation of regression with intercept and coefficient.
2. Can you perform a critical analysis on the data provided and answer the following questions
a. Are there any data abnormalities? How would you suggest the department to work on
data abnormalities?
 item_name: 4 missing values.
 item_description: 135 missing values.
 The correlation matrix shows low correlation between price, stock, and sold count.
This suggests that multicollinearity may not be a significant concern in these
variables.
b. Exploratory Analysis – chose any two KPIs
c. Statistical Analysis and interpret the results.
d. Can we normalize data?
 YES we can normalize data by removing null values from items and item description.
e. How can we recommend growth and improvements to the organization.
 The relationship between price and Revenue suggests reviewing pricing strategies.
 To enhance revenue, it is crucial to analyze and optimize the correlation between
product sales and pricing strategies. Utilizing data analytics for strategic decisionmaking can significantly improve both the volume of sales and overall profitability.
Ans 1: