Statistics for Data science

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Price: 19.99$

When you talk about data science the most important thing is  Statistical MATHS. This course teaches statistical maths using simple excel. My firm belief is MATHS is 80% part of data science while programming is 20%. If you start data science directly with python , R and so on , you would be dealing with lot of technology things but not the statistical things. I recommend start with statistics first using simple excel and the later apply the same using python and R. Below are the topics covered in this course. Lesson 1:- What is Data science ?Chapter 1:- What is Data science  and why do we need it ?Chapter 2:- Average , Mode , Min and Max using simple Excel. Chapter 3:- Data science is Multi-disciplinary. Chapter 4:- Two golden rules for maths for data science. Lesson 2:- What is Data science ?Chapter 4:- Spread and seeing the same visually. Chapter 5:- Mean, Median, Mode, Max and Min Chapter 6:- Outlier, Quartile & Inter-Quartile Chapter 7:- Range and Spread Lesson 3 – Standard Deviation, Normal Distribution & Emprical Rule. Chapter 8:- Issues with Range spread calculation Chapter 9:- Standard deviation Chapter 10:- Normal distribution and bell curve understanding Chapter 11:- Examples of Normal distribution Chapter 12:- Plotting bell curve using excel Chapter 13:- 1 , 2 and 3 standard deviation Chapter 14:- 68,95 and 98 emprical rule. Chapter 15:- Understanding distribution of 68,95 and 98 in-depth. Lesson 4:- The ZScore calculation Chapter 16:- Probability of getting 50% above and 50% less. Chapter 17:- Probability of getting 20 value. Chapter 18:- Probability of getting 40 to 60. Lesson 5 – Binomial distribution Chapter 22:- Basics of binomial distribution. Chapter 23:- Calculating existing probability from history. Chapter 24:- Exact vs Range probability. Chapter 25:- Applying binomial distribution in excel. Chapter 26:- Applying Range probability. Chapter 27:- Rules of Binomial distribution.