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Learning AI
Machine Learning cơ bản
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Data analysing softwares
Statistical Modeling and Hypothesis Testing in R
0 students
Last updated
Aug 2025
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Overview
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About the course
Statistical Modeling and Hypothesis Testing in R
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Course content
Sections:
4
•
Activities:
1
•
Resources:
27
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Section 1
Perform Hypothesis Testing for Data-driven Decisions
Announcements
001 System and Software Requirements 8WKt gitir
002 Hypothesis Testing whn7 gitir
003 Statistical Testing K9xI gitir
004 T tests eZHL gitir
005 Demo Two sample T test sdET gitir
006 Demo Paired Samples T test and the Wilcoxon Signed rank Test yWYL gitir
007 ANOVA PBpB gitir
008 Demo ANOVA and Tukey s HSD qx4m gitir
009 Demo Kruskal Wallis Test and Dunn s Test SJdv gitir
010 MANOVA pOSt gitir
011 Demo MANOVA cM39 gitir
012 Pearson s Chi2 Test U9b6 gitir
013 Demo Chi2 Test Gfwz gitir
Section 2
Build and Interpret Statistical Models
014 Linear Regression g7Yv gitir
015 Demo Linear Regression G2xQ gitir
016 Genaralized Linear Models E2AN gitir
017 Demo Logistic Regression Rb3l gitir
018 Demo Poisson Regression 30JK gitir
Section 3
Apply Advanced Statistical Techniques
019 Mixed effects Models kW16 gitir
020 Demo Mixed effects Models p2bq gitir
021 State Models p5d0 gitir
022 Survival Models wGK0 gitir
023 The Kaplan Meier Estimator and the Cox Proportional Hazards Model JAUn gitir
024 Demo Survival Analysis Uhhy gitir
025 Demo Kaplan Meier Analysis ZrqM gitir
026 Demo Cox Proportional Hazards Model hADh gitir
Section 4
Interpret and Communicate Statistical Findings
027 Demo Using Visualizations to Interpret Data 9D7n gitir
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Statistical Modeling and Hypothesis Testing in R
Course modified date:
15 Aug 2025
Statistical Modeling and Hypothesis Testing in R
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