Campus Recruitment: Do you have what it takes?

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Introduction:

Data Cleaning:

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Exploring the dataset (EDA):

Q1. What is the count for each of the categorical variables?

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Q2. Compare placement for three categorical variables i.e Under-Grad Degree Type, MBA Specialization and Work Experience?

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Q3. Is there a Gender-bias in the data?

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Q4. What is the relationship between different numerical variables and what is its direction i.e positive or negative?

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Q5. What is the distribution of salaries for people who did get placed?

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Q6. What is the distribution of percentages for people who got placed and those who did not?

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Machine Learning and Statistical Inference

One-Way ANOVA

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Predicting MBA percentage from Degree Percentage using Simple Linear Regression

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Model for Predicting Student Placement

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Concluding Remarks:

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