09-20-2023, 02:09 AM
Statistics and Hypothesis Testing for Data science
"Mastering Data Analysis and Making Informed Decisions with Statistical Hypothesis Testing in Data Science".
New
Rating: 0.0 out of 5
(0 ratings)
492 students
4.5 hours on-demand video
Description
Welcome to "Statistics and Hypothesis Testing for Data Science" – a comprehensive Udemy course that will empower you with the essential statistical knowledge and data analysis skills needed for success in the world of data science.
Here's what you'll learn:
Delve into the world of data-driven insights and discover how statistics plays a pivotal role in shaping our understanding of information.
Equip yourself with the essential Python skills required for effective data manipulation and visualization.
Learn to categorize data, setting the stage for meaningful analysis.
Discover how to summarize data with measures like mean, median, and mode.
Explore the variability in data using concepts like range, variance, and standard deviation.
Understand relationships between variables with correlation and covariance.
Grasp the shape and distribution of data using techniques like quartiles and percentiles.
Learn to standardize data and calculate z-scores.
Description
Welcome to "Statistics and Hypothesis Testing for Data Science" – a comprehensive Udemy course that will empower you with the essential statistical knowledge and data analysis skills needed for success in the world of data science.
Here's what you'll learn:
Delve into the world of data-driven insights and discover how statistics plays a pivotal role in shaping our understanding of information.
Equip yourself with the essential Python skills required for effective data manipulation and visualization.
Learn to categorize data, setting the stage for meaningful analysis.
Discover how to summarize data with measures like mean, median, and mode.
Explore the variability in data using concepts like range, variance, and standard deviation.
Understand relationships between variables with correlation and covariance.
Grasp the shape and distribution of data using techniques like quartiles and percentiles.
Learn to standardize data and calculate z-scores.
Enjoy!
"Mastering Data Analysis and Making Informed Decisions with Statistical Hypothesis Testing in Data Science".
New
Rating: 0.0 out of 5
(0 ratings)
492 students
4.5 hours on-demand video
Description
Welcome to "Statistics and Hypothesis Testing for Data Science" – a comprehensive Udemy course that will empower you with the essential statistical knowledge and data analysis skills needed for success in the world of data science.
Here's what you'll learn:
Delve into the world of data-driven insights and discover how statistics plays a pivotal role in shaping our understanding of information.
Equip yourself with the essential Python skills required for effective data manipulation and visualization.
Learn to categorize data, setting the stage for meaningful analysis.
Discover how to summarize data with measures like mean, median, and mode.
Explore the variability in data using concepts like range, variance, and standard deviation.
Understand relationships between variables with correlation and covariance.
Grasp the shape and distribution of data using techniques like quartiles and percentiles.
Learn to standardize data and calculate z-scores.
Description
Welcome to "Statistics and Hypothesis Testing for Data Science" – a comprehensive Udemy course that will empower you with the essential statistical knowledge and data analysis skills needed for success in the world of data science.
Here's what you'll learn:
Delve into the world of data-driven insights and discover how statistics plays a pivotal role in shaping our understanding of information.
Equip yourself with the essential Python skills required for effective data manipulation and visualization.
Learn to categorize data, setting the stage for meaningful analysis.
Discover how to summarize data with measures like mean, median, and mode.
Explore the variability in data using concepts like range, variance, and standard deviation.
Understand relationships between variables with correlation and covariance.
Grasp the shape and distribution of data using techniques like quartiles and percentiles.
Learn to standardize data and calculate z-scores.
Enjoy!
