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Data Science-Fundamentals of Statistics
Data science and statistics
Data & Analytics,Statistics,Development,Data Science
Lectures -29
Resources -25
Duration -7 hours
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Course 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
What will you learn in this course:
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
What are the prerequisites for this course?
No requirement is needed. students or anyone who is interested in data analysis can take the course
Curriculum
Check out the detailed breakdown of what’s inside the course
1.Introduction-Data and Statistics
4 Lectures
- 1.1-INTRODUCTION 01:19 01:19
- 1.2-meet the instructor 02:21 02:21
- 1.3_what is statistics 05:25 05:25
- 1.4_about data 15:42 15:42
2.Measure of Central Tendency
3 Lectures
3.Measure of dispersion
2 Lectures
4.Shape of data_measure of Skewness
4 Lectures
5.Measures of relatioship -Correlation and Regresson Analysis
4 Lectures
6.Basic probability and Bayes theorem
2 Lectures
7.Discrete probability distribution-Binomial-Poisson
2 Lectures
8. Continuous probability distribution-normal distribution
2 Lectures
9.Rates-Ratio-OddRatio(OR)
2 Lectures
10.screenig test(Confusion Matrix)
4 Lectures
Instructor Details
Mohammad Rafiqul Islam
Academician and data scientistDr. Mohammad Rafiqul Islam is currently working as a Professor at BRAC University, Dhaka, Bangladesh. He is also working as an Instructor at Udemy, Eduonix. Expert in R, SPSS, Rapidminer and familiar with SQL, Python, STATA, and other programs. He has 26 publications in national and international referred Journals including one book and two book chapters
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