| 1 -00252.pdf | 330.9 KB | ||
| 1 -Basic probability concepts (events, sample space, conditional probability).mp4 | 49.1 MB | ||
| 1 -CAtegoriacalDAtaAnalysis.pdf | 967.9 KB | ||
| 1 -Categorical Data Analysis and Chi Test Introduction.mp4 | 37.8 MB | ||
| 1 -Correlation - Regression and Data Analysis Introduction.mp4 | 14.1 MB | ||
| 1 -Covariance Theory Explain.mp4 | 173.9 MB | ||
| 1 -CovariancePAge.html | 15.2 KB | ||
| 1 -CovariancePAge.pdf | 545.6 KB | ||
| 1 -Descriptive Statistics - Basic Introduction.mp4 | 13.3 MB | ||
| 1 -Hypothesis Testing Fundamentals Concept in Probabilty and Statistics.mp4 | 44.3 MB | ||
| 1 -Image.jpg?042148 | 30 KB | ||
| 1 -Independent samples t-test.mp4 | 20.6 MB | ||
| 1 -IndipendentTest.pdf | 484.8 KB | ||
| 1 -IndipendtentTest.py | 2.8 KB | ||
| 1 -Intent of Course and What You Will learn.mp4 | 7.2 MB | ||
| 1 -IntentOfCOurse.pdf | 591.6 KB | ||
| 1 -Normal Distribution.mp4 | 243.1 MB | ||
| 1 -Normal_.pdf | 721.5 KB | ||
| 2 -008.pdf | 19.2 KB | ||
| 2 -Chi-square test of independence and Chi-square goodness-of-fit test.mp4 | 78.9 MB | ||
| 2 -ChiQuadro.pdf | 652.7 KB | ||
| 2 -Covariance Exercise with Python.mp4 | 71.4 MB | ||
| 2 -First Exemple.mp4 | 14.9 MB | ||
| 2 -Introduction.mp4 | 89.4 MB | ||
| 2 -Kitest_.py | 3.3 KB | ||
| 2 -Normal Distrubution Excercise.mp4 | 67.1 MB | ||
| 2 -Null and alternative hypotheses.mp4 | 46.1 MB | ||
| 2 -Paired samples t-test.mp4 | 29.9 MB | ||
| 2 -PairedTest.pdf | 504 KB | ||
| 2 -Principal Theme.pdf | 64.2 KB | ||
| 2 -Random variables.mp4 | 21.8 MB | ||
| 2 -Types of data (qualitative, quantitative, nominal, ordinal, interval, ratio).mp4 | 33.3 MB | ||
| 2 -Understandig TypeOfDAta.pdf | 458.9 KB | ||
| 2 -What is Data Science and Statistics.mp4 | 48.7 MB | ||
| 2 -hyper.pdf | 226.5 KB | ||
| 3 -ANOVA (One-way, Two-way).mp4 | 46.3 MB | ||
| 3 -Anova_Test.pdf | 512.4 KB | ||
| 3 -Anova_Test_app2.py | 2.5 KB | ||
| 3 -Common probability distributions (Bernoulli, Binomial, Poisson, Normal, t-distri.mp4 | 45.2 MB | ||
| 3 -ContigentTAble.pdf | 440.9 KB | ||
| 3 -Contingency tables.mp4 | 37.5 MB | ||
| 3 -Correlation coefficients (Pearson, Spearman).mp4 | 61.6 MB | ||
| 3 -Infographic.pdf | 638.2 KB | ||
| 3 -Introduction to Python Lybraries - Anaconda and Streamlit use.mp4 | 62.9 MB | ||
| 3 -Measures of central tendency (mean, median, mode).mp4 | 70.5 MB | ||
| 3 -StreamLitApplication.py | 5.5 KB | ||
| 3 -nuovo 150 (1).pdf | 410.4 KB | ||
| 3 -tg_ (1).pdf | 427.3 KB | ||
| 4 -005.pdf | 404.9 KB | ||
| 4 -Central Limit Theorem.mp4 | 36.4 MB | ||
| 4 -EXCERCISE001.csv | 102.4 B | ||
| 4 -Error estimation in Statistical Data Analysis.mp4 | 38.2 MB | ||
| 4 -ErrorEstimation.pdf | 359.9 KB | ||
| 4 -Exx001.py | 1.2 KB | ||
| 4 -Import and Read Csv Data in Python Script.mp4 | 44.7 MB | ||
| 4 -Infograpfic CentralThoery.pdf | 494.6 KB | ||
| 4 -LinearRegression.pdf | 640.1 KB | ||
| 4 -Linear_REgression_ScratchCode.py | 4.7 KB | ||
| 4 -Manning_Whytnnei_Test.py | 2.7 KB | ||
| 4 -Measures of dispersion (range, variance, standard deviation, IQR).mp4 | 34.6 MB | ||
| 4 -Measures of dispersion.pdf | 448.9 KB | ||
| 4 -Non-parametric tests (Mann-Whitney U, Wilcoxon signed-rank, Kruskal-Wallis).mp4 | 37.2 MB | ||
| 4 -NonParameticTEst.pdf | 493.4 KB | ||
| 4 -ReadCSvData.mp4 | 60.9 MB | ||
| 4 -Simple Linear Regression.mp4 | 23.6 MB | ||
| 4 -SimpleLinearRegression.pdf | 728.5 KB | ||
| 4 -StreamLitApp.py | 2 KB | ||
| 5 -Hyn.pdf | 526.4 KB | ||
| 5 -Multiple Linear Regression.mp4 | 36.4 MB | ||
| 5 -Shape of distributions (skewness, kurtosis).mp4 | 21.6 MB | ||
| 5 -The Shape of Distributions.pdf | 343.7 KB | ||
| 6 -Data visualization (histograms, box plots, bar charts, scatter plots) - Python.mp4 | 20.7 MB | ||
| 6 -DataVisualization__.pdf | 397.2 KB | ||
| 6 -Introduction to Logistic Regression (for binary outcomes).mp4 | 23.7 MB | ||
| 6 -Introduction to Logistic Regression_.pdf | 396.8 KB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 77 total files | |||
Statistics with python
https://WebToolTip.com
Published 8/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 57m | Size: 1.77 GB
Unlocking Data Insights: Statistics with R and Python
What you'll learn
Introduction to Data and Programming Environments
Descriptive Statistics
Probability and Probability Distributions
Sampling and Estimation
Hypothesis Testing Fundamentals
Comparing Groups
Categorical Data Analysis
Correlation and Regression
Requirements
Math
Pc use
Description
Welcome to "Statistics with R and Python," your gateway to mastering the art and science of data analysis with Ai Tools Engeneering- In today's data-driven world, the ability to extract meaningful insights is crucial, and this course provides you with the skills to do so, leveraging two of the most powerful tools in a data professional's arsenal: R and Python. This course is meticulously designed for hands-on learning. You'll begin by building a solid foundation in descriptive statistics and data visualization, transforming raw data into compelling narratives using libraries like ggplot2, Matplotlib, and Seaborn. We then delve into inferential statistics, guiding you through the principles of probability, hypothesis testing, and confidence intervals, enabling you to draw valid conclusions from your data. A significant portion of the course is dedicated to regression analysis, where you'll learn to build and interpret linear and logistic models for forecasting and understanding relationships. Through hands-on exercises and real-world case studies, you'll gain expertise in data cleaning, manipulation, and analysis workflows. By the end of this journey, you'll not only understand statistical concepts but also possess the practical coding skills in both R and Python to effectively apply them across various domains. Join us to transform data into actionable insights! Use data with AI apps to build reliable statistical predictions and get closer to the world of machine learning.“This course contains the use of artificial intelligence.”
Who this course is for
Engeneering
Math
| torrent name | size | uploader | age | seed | leech |
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| 2.4 GB | freecoursewb | 1 month | 1 | 35 | |
| 1.4 GB | freecoursewb | 1 month | 1 | 70 | |
| 3.7 GB | freecoursewb | 1 month | 1 | 18 | |
| 775.5 MB | freecoursewb | 1 month | 0 | 0 | |
| 3.8 GB | freecoursewb | 1 month | 1 | 79 |
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