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Data Science from Scratch for Beginners: Data Analysis Techniques, Method

Statistics & Applied Data Science – Business Data Analysis

Data Science Statistics: Data Science from Scratch for Beginners: Data Analysis Techniques, Method Course: Analytics

What you’ll learn

Statistics & Applied Data Science – Business Data Analysis

  • Data analysis FAQ related to interview questions in your career.
  • Four main things you should know them in data analysis and business analysis
  • HYPOTHESIS TESTING
  • Normal distribution and standard normal in detail using the Z table.
  • Sampling distribution with practical simulation apps and answering of important technical questions.
  • Confidence level and Confidence interval .
  • What is t distribution? ( with projects )
  • Inferential and Descriptive statistics with a collection of important quizzes and examples.
  • One sample means a t-test.
  • Two sample means t-test.
  • How to calculate P-value using manual and direct method?
  • What is after data analysis?
  • TWO PROJECTS  related to hypothesis testing
  • Null hypothesis and alternative hypothesis.
  • What is the P-value?
  • Data types and Why we need to study data types?
  • What is Type one error?
  • Relationship between Type one error and Alpha ( not confident probability )
  • Is Normal distribution and t distributions are cousins?
  • Projects like Estimation of goals in the premier league ( using confidence interval ), and more .. and more to learn it
  • Ice Cola example with student’s t distribution.
  • Help fisherman to catch Tuna using the sampling distribution
  • Is programming something mandatory to learn data analysis and business analysis?
  • Which programming languages I should start with it?
  • Practical significance versus statistical significance, and more to learn .. and more to learn it

Requirements

  • I will start from level ZERO and gradually step by step I will make you at an advanced level.

Description

270+ video lectures include real-life practical projects and examples for people need to learn statistics for Machine learning and Data Analysis.

All of these jobs above need learning STATISTICS.

Who prepared this course material? Statistics & Applied Data Science – Business Data Analysis

After hard work from five months ago, we created +270 Lectures/Articles to cover everything related to practical statistics.  
In no time with a simple and easy way, you will learn and love statistics.
We stress in this course to make it very spontaneous to make all students love statistics. 

Who’s teaching you in this course?
Also, I worked as a Tutor and consultant trainer with a leading international company located in the USA and UK.

I spent over five months of hard-working to create +270 lectures/Articles with high quality to make all students enjoy and love statistics.
I’m sharing a lot of practical experiencefrom my work with you in this course.

What is my final goal after my students enroll in this course? My final goal is to make all students and engineers love practical statistics.
My big challenge in this course is to make it a professional course at the same time it should be very easy and simple for all People.
Therefore you will notice that I used a lot of  graphics and imaginary ideas to make you LOVE DATA ANALYSIS    

What are the course contents?

  • Starting with FAQ related to interview questions in your career.
  • What is after data analysis?
  • Descriptive statistics with a collection of important quizzes and examples.
  • Normal distribution and standard normal in detail using Z table .
  • Sampling distribution with practical simulation apps and answering of important technical questions.
  • Confidence level and Confidence interval.
  • what is t distribution? ( with examples )
  • What is DEGREE OF FREEDOM? ( with examples )
  • One tail and two tail in Confidence level.

Awesome Projects and examples like :

  1. How Mr. Genie helped us to find all the fishes in the sea?
  2. Mr. Genie power versus statistics power
  3. The double-edged sword of statistics
  4. Help fisherman to catch Tuna using the sampling distribution
  5. Ice Cola example with student’s t distribution.
  6. Estimation of goals in the premier league ( using confidence interval ).

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Who this course is for:

  • People searching for jobs in data analysis and data science
  • People searching for jobs in business analysis and business intelligence
  • Business managers and business directors
  • practical statistics in data analysis
  • Anyone needs to learn statistics from beginner to advanced level.
  • Statistics for data science
  • Statistics for data analysis
  • Marketing analyst
  • AP statistics
  • Machine learning
  • beginner in business intelligence
  • data science
  • Hypothesis testing
  • Content From: https://www.udemy.com/course/ureadup_sds/

Statistics & Applied Data Science – Business Data Analysis

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