Udemy - Learn Hypothesis Testing With Python - Printable Version +- Softwarez.Info - Software's World! (https://softwarez.info) +-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone) +--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials) +--- Thread: Udemy - Learn Hypothesis Testing With Python (/Thread-Udemy-Learn-Hypothesis-Testing-With-Python)

Udemy - Learn Hypothesis Testing With Python - OneDDL - 03-12-2025 Free Download Udemy - Learn Hypothesis Testing With Python Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 2.93 GB | Duration: 7h 57m to succeed in your career What you'll learn Learn avout visualisations, how to code them in Python, and how they enhance the presentation of your work. Learn anout the measure of central tendency, which is composed of the mean, median, and mode of a dataset. Learn about the measure of dispersion, which calculates the spread and standard deviation of a dataset. Learn about the various measures of association and some of the statistical tests that it is comprised of. Learn about probability theory and how it is an integral part of hypothesis testing. Learn about probability distributions and four popular distributions that are used in hypothesis testing. Learn about the central limit theorem, whict is integral to the study of statistics. Learn about confidence intervals, which are an important concept in hypothesis testing. Learn about hypothesis testing and how to perform them. Learn about difference of means tests and how to perform them. Requirements The learner should have a basic understanding of statistics. The learner should have a basic understanding on the Python programming language. Description In today's data-driven world, learning hypothesis testing is essential for several reasons, to include:1. Informed Decision-Making: Hypothesis testing helps individuals make decisions based on data rather than intuition or guesswork. Whether it's in business, healthcare, education, or everyday life, making decisions backed by statistical evidence ensures more accurate and reliable outcomes.2. Critical Thinking: Understanding hypothesis testing fosters critical thinking skills. It encourages individuals to question assumptions, analyze data rigorously, and draw conclusions based on empirical evidence. This skill is valuable in evaluating the credibility of information and avoiding biases.3. Professional Advantage: Many professions, such as data analysis, scientific research, marketing, and finance, require a solid understanding of hypothesis testing. Mastering this skill can enhance career prospects and open doors to opportunities in fields that rely on data analysis and evidence-based decision-making.4. Enhanced Research Skills: Hypothesis testing is a fundamental aspect of scientific research. By learning how to formulate and test hypotheses, individuals can contribute to advancing knowledge in various domains, from medicine to social sciences. It also enables them to critically assess research studies and their findings.5. Policy and Program Evaluation: Hypothesis testing is crucial for evaluating the effectiveness of policies, programs, and interventions. Governments and organizations use it to determine whether initiatives are producing the desired outcomes and to make data-informed decisions for improvements.6. Empowerment in Daily Life: Understanding hypothesis testing empowers individuals to interpret data presented in news, reports, and studies. It helps them make informed choices about personal health, finances, and other aspects of life by discerning valid conclusions from misleading claims.7. Technological Integration: With the rise of big data and artificial intelligence, hypothesis testing has become even more relevant. It forms the backbone of machine learning models and algorithms, enabling the extraction of meaningful insights from vast datasets.8. Reduction of Misinformation: In an era of information overload, knowing hypothesis testing helps combat misinformation. It equips individuals with the tools to critically evaluate the validity of claims and distinguish between scientifically sound information and pseudoscience.In summary, learning hypothesis testing equips individuals with the skills needed to navigate a complex and data-rich world. It promotes informed decision-making, critical thinking, professional development, and a deeper understanding of the world around us.in this course the student will learn how to conduct several hypothesis testing scenerious using the general purpose language, Python. the student will learn about:-1. Visualisation techniques that are important in statistical research, with a special emphasis on hypothesis testing.2. Specific staistical measurements that are important when carrying out a hypothesis test.3. the theory of probability and distribution, with a special emphasis ob the distributions that are used in hypothesis testing.4. the student will learn the Python code of a multitude of practice problems in probability, confidence intervals,hypothesis testing, and difference in means testing. Overview Section 1: Introduction Lecture 1 Introduction Section 2: Charts Lecture 2 charts Lecture 3 line chart Lecture 4 bar chart Lecture 5 pie chart Lecture 6 scatter plot Lecture 7 box plot Lecture 8 histogram Lecture 9 QQ plot Section 3: Measure of central tendency Lecture 10 measure of central tendency Section 4: Measure of dispersion Lecture 11 measure of dispersion Section 5: Measure of association Lecture 12 measure of association Lecture 13 pearson correlation coefficient Lecture 14 spearman rank coefficient Lecture 15 chi2 test of independence Lecture 16 cramers v Lecture 17 odds ratio Lecture 18 linear regression Lecture 19 contingency coefficient Lecture 20 special considerations Lecture 21 logistic regression Section 6: Probability theory Lecture 22 probability theory Section 7: distributions theory Lecture 23 distribution theory Lecture 24 symmetrical distribution Lecture 25 left skewed distribution Lecture 26 right skewed distribution Section 8: Probability distributions Lecture 27 probability distributions Lecture 28 normal distribution Lecture 29 binomial distribution Lecture 30 poisson distribution Lecture 31 t distribution Lecture 32 summary of distributions Section 9: Central limit theorem Lecture 33 central limit theorem Section 10: Practice problems using the normal distribution Lecture 34 loaves of bread Lecture 35 test scores Lecture 36 heights Lecture 37 male heights Lecture 38 manufacturing Lecture 39 sandwiches Section 11: Practice problems using the binomial distribution Lecture 40 dice rolls Lecture 41 tax returns Lecture 42 light bulbs Lecture 43 sports Lecture 44 customer service Lecture 45 pass or fail Section 12: Practice problems using the Poisson distribution Lecture 46 convenience store Lecture 47 coffee shop Lecture 48 defective parts Lecture 49 traffic accidents Lecture 50 help desk Lecture 51 hotel bookings Section 13: Practice poblems with the t distribution Lecture 52 test scores Lecture 53 researcher Lecture 54 drug trials Lecture 55 diet Lecture 56 machines Section 14: Confidence intervals Lecture 57 confidence intervals Lecture 58 house prices and sales Lecture 59 ceo management succession plan Lecture 60 defective batteries Lecture 61 political pollster Lecture 62 teaching methods Section 15: Hypothesis tests Lecture 63 hypothesis testing Lecture 64 bottles Lecture 65 miles per gallon Lecture 66 batteries Lecture 67 software Lecture 68 drugs Lecture 69 men's mba ages Lecture 70 tea or coffee? Lecture 71 masks Lecture 72 lunch Section 16: Difference in means tests Lecture 73 difference in means tests Lecture 74 olympian heights Lecture 75 male and female heights Lecture 76 company salaries Lecture 77 blood pressure Lecture 78 ages of men and women mba students Section 17: End of course Lecture 79 Congratulations for completing the course This course is intended for researchers who would like to know how to perform hypothesis tests.,This course is intended for students would would like to learn more about statistics.,This course is intended for Python programmers wou would like to know more about the statistical and scientific libraries that can be used with the language. Homepage: [To see links please register or login] DOWNLOAD NOW: Udemy - Learn Hypothesis Testing With Python Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live [To see links please register or login] No Password - Links are Interchangeable