Statistics for Data Science Complete Crash course for beginners in urdu/hindi

✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ Codes: https://github.com/AammarTufail/python-ka-chilla-2024/tree/main/06_statistics ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ Welcome to the Statistics for Data Science Complete Crash Course for Beginners in Urdu/Hindi! 🎓 This comprehensive course is designed for those who are new to data science and want to master statistics—the foundation of data analysis, machine learning, and AI. In this video, you’ll learn everything you need to get started, from basic concepts to advanced statistical techniques, all explained in simple Urdu/Hindi for easy understanding. 🌟 What You'll Learn: Introduction to Statistics - Why statistics is essential in data science. Descriptive Statistics - Mean, median, mode, standard deviation, and more. Probability Basics - Understanding probability, distributions, and events. Inferential Statistics - Hypothesis testing, confidence intervals, p-values, etc. Regression Analysis - Simple linear regression, multiple regression, and their applications. Correlation and Causation - Understanding relationships between variables. Applications in Data Science - How statistics is applied in data analysis and machine learning. This course is perfect for beginners who want to dive into data science with a solid foundation in statistics. Whether you're a student, professional, or just curious about data science, this course will equip you with the knowledge and skills to start analyzing data effectively. 📈 Why Watch This Video? Simplified Explanations - Concepts broken down in simple Urdu/Hindi language. Hands-On Examples - Practical examples to understand how statistics applies to data science. Real-World Applications - Learn how statistics powers decisions in business, technology, healthcare, and more. 👉 Don’t forget to like, subscribe, and hit the bell icon for more educational content on data science, machine learning, and programming in Urdu/Hindi! 📌 Recommended For: Beginners in Data Science Students studying statistics Professionals looking to build a foundation in data analysis Anyone interested in learning data science in Urdu/Hindi #StatisticsForDataScience #DataScienceCrashCourse #BeginnersGuide #StatisticsInUrdu #DataScienceInHindi #StatisticsCourse #DescriptiveStatistics #ProbabilityBasics #InferentialStatistics #RegressionAnalysis #DataScienceLearning #MachineLearningBasics #DataScience2024 #UrduAI #Pakistan #PythonKaChilla Chapters: 00:00:00 Introduction to statistics for Data Science 00:08:03 What is statistics? 00:14:06 Content of this course 00:22:15 Why statistics is important? 00:29:29 Scales of measurement 00:46:55 Qualitative vs. Quantitative data 00:56:32 Discrete, Continuous or Binary Data 01:03:28 Time series Data 01:06:31 Spatial Data 01:08:55 Categorical vs. Ordinal Data 01:13:37 Multivariate Data 01:16:38 Structured vs. Unstructured Data 01:26:12 Boolean Data 01:27:29 Operationalization and Proxy measurements 01:35:53 True vs. Error Score 01:46:23 Types of Errors 01:57:44 Type-I vs. Type-II errors 02:09:42 Reliability and Validity 02:25:21 Triangulation 02:40:52 Surrogate Endpoints 02:50:19 Measurement and Data Bias 03:18:17 How to remove Bias? 03:26:56 Statistics and Types of Statistics 03:45:14 Why statistics is important to learn? 03:55:52 Types of Data Analysis 04:11:34 Assignment Alert 04:14:40 Central Tendency 04:25:13 Mean, types and limitations of means 04:54:36 Median 05:07:30 Mode 05:22:47 Population vs. Sample means 05:29:29 Variation, spread or dispersion in data 05:50:30 Data variability and Range 05:59:58 Interquartile Range (IQR) 06:17:37 Variance 06:30:17 Standard Deviation vs. Standard Error 06:54:19 Normal Distribution and Standard Deviation 07:01:05 Data Distribution and its types 07:46:29 Skewness vs. Kurtosis 08:31:59 Primary vs. Secondary Data 08:45:42 Data Collection and Sampling 09:02:05 Best practices for Data Collection 09:12:04 Sampling Types 09:24:02 All sampling Techniques 09:34:29 Hybrid Sampling 09:35:01 Descriptive Statistics 09:51:01 Descriptive statistics with t-test 10:09:53 How to choose right statistical method? 10:33:32 Exploratory Data Analysis (EDA) 10:38:35 Dependent vs. Independent Variables 10:48:34 Inferential Statistics 10:55:51 Hypothesis and Hypothesis Testing 11:16:53 Confidence Intervals 11:26:59 Chi-squared test and Python code 11:40:28 Shapiro Wilk Test in python 11:48:51 t-tests in python 12:00:58 Leven’s test for homogeneity 12:05:17 One-way ANOVA 12:10:13 ANOVA in Python 12:37:56 MANOVA in python 12:43:51 Correlation in python 12:59:31 Case Study-I (Chi-squared test) 13:18:22 Case Study-II (t-tests) 13:35:10 Case Study-II (ANOVA) 13:54:49 Case Study-IV (Correlation) 14:09:29 Basic Pillars of EDA 14:13:47 Free Book as Bonus Resource 14:14:38 Python ka Chilla 2024-25 ✅Our Free Books: https://codanics.com/books/abc-of-statistics-for-data-science/ #codanics #dataanalytics #pythonkachilla #pkc24 ✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅✅ Python ka chilla 2024: https://forms.gle/kUU3eZJsFRb7Cn6r8