KIMS Hospital Clinical Pharmacologist Interview Questions and Answers

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Q1. What is one-hot encoding?
Ans. 
One-hot encoding is a technique used to convert categorical variables into a numerical format for machine learning algorithms.
• It creates a binary column for each category in the variable, with 1 indicating the presence of the category and 0 indicating absence.

• One-hot encoding is commonly used in machine learning models to handle categorical data such as gender, color, or country.

• For example, if a 'color' variable has c...read more
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Q1. What is the main difference between data mining and data analysis?
Ans. 
Data mining involves discovering patterns and relationships in large datasets, while data analysis focuses on interpreting and drawing insights from data.
• Data mining is the process of extracting useful information from large datasets.

• Data analysis involves examining and interpreting data to draw conclusions and make informed decisions.

• Data mining uses techniques like clustering, classification, and association to disco...read more
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Q2. What is data validation?
Ans. 
Data validation is the process of ensuring that data is accurate, complete, and consistent.
• Data validation involves checking data for errors, inconsistencies, and anomalies.

• It helps to ensure data quality and reliability.

• Validation can be done through various techniques such as range checks, format checks, and cross-field validation.

• Examples of data validation include verifying that a phone number has the correct numbe...read more
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Q3. Explain the main steps involved in data analysis ?
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Data analysis involves several steps including data collection, data cleaning, data exploration, data modeling, and data visualization.
• Data collection: Gathering relevant data from various sources.

• Data cleaning: Removing any errors, inconsistencies, or missing values from the data.

• Data exploration: Analyzing the data to understand its characteristics and identify patterns or trends.

• Data modeling: Applying statistical o...read more
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Q4. Explain what data cleansing is
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Data cleansing is the process of identifying and correcting or removing errors, inconsistencies, and inaccuracies in datasets.
• Data cleansing involves identifying and handling missing values in datasets.

• It also includes removing duplicate records or entries.

• Data cleansing may involve correcting spelling mistakes or formatting issues in data.

• It helps improve data quality and reliability for analysis and decision-making.

• E...read more
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Q1. Why do you want to work at our company
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Assignments based on data analyst

It help me to increase my knowledge

Able to learn new things

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