## Data Science-Fundamentals of Statistics

Data science and statistics

#### Description

• Students will gain knowledge about the basics of statistics
• They will have a clear understanding of different types of data with examples which is very important to understand data analysis
• Students will be able to analyze, explain and interpret the data
• They will understand the relationship and dependency by learning Pearson's correlation coefficient, scatter diagram, and linear regression analysis between the variables and will be able to know to make the prediction
• Students will understand the different methods of data analysis such as a measure of central tendency (mean, median, mode), a measure of dispersion (variance, standard deviation, coefficient of variation), how to calculate quartiles, skewness, and box plot
• They will have a clear understanding of the shape of data after learning skewness and box plot, which is an important part of data analysis
• Students will have a basic understanding of probability and how to explain and understand Bayes theorem with the simplest example
• Students will have a basic understanding of discrete probability distribution such as Binomial, Poisson and continuous probability distribution such as normal distribution with details example
• They will come to know about rates, ratios, odd ratios, and screening test
• They will have clear knowledge about screening tests and confusion matrix with details example
• They will gain a clear idea of the fundamentals of statistics
• Especially, those who are interested to advance their careers in data science and machine learning should complete the course

#### Goals

• Students will be able to analyze, explain and interpret the data

• They will understand the relationship and dependency between the data and how to make the prediction

• Students will understand the different methods of data analysis such as a measure of central tendency (mean, median, mode), a measure of dispersion (variance, standard

• Students will have a basic understanding of probability and Bayes theorem

• They will come to know about rates, ratios, odd ratios, and screening test

#### Prerequisites

• No requirement is needed. students or anyone who is interested in data analysis can take the course

#### Curriculum

• 1.1-INTRODUCTION
01:19
Preview
• 1.2-meet the instructor
02:21
Preview
• 1.3_what is statistics
05:25
15:42
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##### This Course Includes
• 7 hours
• 29 Lectures
• 25 Resources
• Completion Certificate