Coursera - Data Analysis with R Specialization

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Free Download Coursera - Data Analysis with R Specialization
Last updated 7/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 84 Lessons ( 11h 23m ) | Size: 1.79 GB
Master Data Analysis with R. Statistical mastery of data analysis including basic data visualization, statistical testing and inference, and linear modeling

What you'll learn
Analyze and visualize data
Perform hypothesis tests, interpret statistical results (e.g., p-values), and report the results of your analysis to clients
Fit, examine, and utilize regression models to examine relationships between multiple variables
Install and use R and RStudio
Skills you'll gain
Probability And Statistics
Correlation And Dependence
Data Analysis
Linear Regression
Statistical Inference
Statistical Hypothesis Testing
Data Visualization
R Programming
Rstudio
Regression Analysis
Exploratory Data Analysis
General Statistics
In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.
Applied Learning Project
You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions.
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238.57 MB | 00:09:37 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

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01 introduction-to-data-analysis-with-r (6.5 MB)
02 the-problem (6.18 MB)
03 understanding-the-data (6.14 MB)
04 r-packages-for-data-science (7.77 MB)
05 importing-and-exporting-data-in-r (9.68 MB)
06 getting-started-analyzing-data-in-r (5.29 MB)
01 pre-processing-data-in-r (3.28 MB)
02 dealing-with-missing-values-in-r (13.08 MB)
03 data-formatting-in-r (6.8 MB)
04 data-normalization-in-r (7.4 MB)
05 binning-in-r (5.83 MB)
06 turning-categorical-values-to-a-numeric-variable-in-r (6.29 MB)
01 descriptive-statistics (9.41 MB)
02 grouping-data-in-r (7.89 MB)
03 analysis-of-variance-anova-in-r (9.87 MB)
04 correlation-in-r (8.48 MB)
05 correlation-statistics (9.62 MB)
01 introduction-to-model-development (4.75 MB)
02 simple-linear-regression (13.46 MB)
03 multiple-linear-regression (6.95 MB)
04 assessing-models-visually (13.38 MB)
05 polynomial-regression (6.63 MB)
06 assessing-the-model (8.92 MB)
07 prediction-and-decision-making (8.74 MB)
01 model-evaluation (14.68 MB)
02 overfitting-and-underfitting (11.93 MB)
03 regularization (11.85 MB)
04 grid-search (7.29 MB)

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