What is left skewed distribution and right skewed distribution? Variance is the square of standard deviationġ3. It represents how far are the data points from the mean What is the meaning of standard deviation? What is the benefit of using box plot?Ĭan be used to compare group of histogramsġ2. Where, Q1 is the first quartile (25 percentile)ġ1. Where, Q3 is the third quartile (75 percentile) How to calculate range and interquartile range? Qualitative data is also known as categorical dataĩ. Quantitative data is also known as numeric data What is quantitative data and qualitative data? Outlier – An outlier is an abnormal valueĨ.Right skewed – the right tail is longer than the left side.Left skewed – the left tail is longer than the right side.Symmetric – the part of the distribution that is on the left side of the median is same as the part of the distribution that is on the right side of the median.Shape – the shape of the data can be symmetric or skewed.Range / IQR / Standard Deviation / Variance are the most commonly used as measures. The disadvantage of using Mode is that there may be more than one mode. Mode – the number that occurs the most.Mean / Median / Mode are the most commonly used as measures. Most common characteristics used in descriptive statistics? We cannot work on the population either due to computational costs or due to availability of all data points for the population.įrom the sample we calculate the statisticsįrom the sample statistics we conclude about the populationĭescriptive statistic is used to describe the data (data properties)ĥ-number summary is the most commonly used descriptive statisticsħ. What is the difference between population and sample in inferential statistics?įrom the population we take a sample. Inferential statistics – provides information of a sample and we need to inferential statistics to reach to a conclusion about the population.ĥ. What is the difference between inferential statistics and descriptive statistics?ĭescriptive statistics – provides exact and accurate information. What are the four main things we should know before studying data analysis?ĭistributions (normal distribution / sampling distribution)Ĥ. Machine learning, on the other hand, requires basic knowledge of coding and strong knowledge of statistics and business.īig data has 3 major components – volume (size of data), velocity (inflow of data) and variety (types of data)ģ. What is the difference between data analysis and machine learning?ĭata analysis requires strong knowledge of coding and basic knowledge of statistics.Part 1 – Basic Statistics and Distributions 20 Question Interview Questions For A Data Engineer Job Profile Most Frequently Asked Questions In Data Science Interview Most Popular Python Interview Questions You Must Prepare For Most Commonly Asked NLP Interview Questions For Beginners Important Pandas Interview Questions Every Beginner Must Know Mathematical Concepts Every Data Scientist Should Master Before An Interview Most Common SQL Questions & Answers You Must Know For Your Next Interviewįrequently Asked Interview Questions For Machine Learning In 2019 Here are some other interview questions resources Here are 40 most commonly asked interview questions for data scientists, broken into basic and advanced. Cracking interviews especially where understating of statistics is needed can be tricky. We frequently come out with resources for aspirants and job seekers in data science to help them make a career in this vibrant field.
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