# Choose between practical significance or statistical significance ?

A free video tutorial from Mahmoud Ali
System analyst , Senior Consultant , President of UreadUp
3.4 instructor rating • 1 course • 6,991 students

## Lecture description

Data Analysis & statistics course Description

Statistics & Applied Data Science - Business Data Analysis

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

09:05:25 of on-demand video • Updated May 2020

• 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 details 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 projects )
• Inferential and Descriptive statistics with collection of important quizzes and examples .
• One sample mean 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 P value ?
• Data types and Why we need to study data types ?
• What is Type one error ?
• Relationship between Type one error and Alpha ( non confident probability )
• Is Normal distribution and t distributions are cousins ?
• Projects like Estimation of goals in 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 sampling distribution
• What is "double edged sword of statistics" ?
• Is programming something mandatory to learn data analysis and business analysis ?