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[DesireCourse.Net] Udemy - Applied Statistical Modeling for Data Analysis in R
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66个文件
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1.34 GB
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2020-1-6 09:36
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2024-11-26 16:36
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[DesireCourse.Net] Udemy - Applied Statistical Modeling for Data Analysis in R.torrent
1. Introduction to the Basics of Applied Statistical Modelling/1. Introduction to the Instructor and Course.mp428.74MB
1. Introduction to the Basics of Applied Statistical Modelling/3. Statistics in the Real World.mp425.28MB
1. Introduction to the Basics of Applied Statistical Modelling/4. Designing Studies & Collecting Good Quality Data.mp420.9MB
1. Introduction to the Basics of Applied Statistical Modelling/5. Different Types of Data.mp49.36MB
1. Introduction to the Basics of Applied Statistical Modelling/6. Conclusion to Section 1.mp48.54MB
2. Section 2 The Essentials of the R Programming Language/2. Introduction to the R Statistical Software & R Studio.mp427.73MB
2. Section 2 The Essentials of the R Programming Language/3. Different Data Structures in R.mp430.53MB
2. Section 2 The Essentials of the R Programming Language/4. Reading in Data from Different Sources.mp442.59MB
2. Section 2 The Essentials of the R Programming Language/5. Indexing and Subsetting of Data.mp428.54MB
2. Section 2 The Essentials of the R Programming Language/6. Data Cleaning Removing Missing Values.mp440.54MB
2. Section 2 The Essentials of the R Programming Language/7. Exploratory Data Analysis in R.mp448.24MB
2. Section 2 The Essentials of the R Programming Language/8. Conclusion to Section 2.mp45.42MB
3. Statistical Tools to Learn More About Your Data/2. Measures of Center.mp417.01MB
3. Statistical Tools to Learn More About Your Data/3. Measures of Variation.mp412.65MB
3. Statistical Tools to Learn More About Your Data/4. Charting & Graphing Continuous Data.mp417.81MB
3. Statistical Tools to Learn More About Your Data/5. Charting & Graphing Discrete Data.mp436.38MB
3. Statistical Tools to Learn More About Your Data/6. Deriving Insights from QualitativeNominal Data.mp421.14MB
3. Statistical Tools to Learn More About Your Data/7. Conclusions to Section 3.mp45.29MB
4. Probability Distributions/1. Background.mp48.36MB
4. Probability Distributions/2. Data Distribution Normal Distribution.mp49.6MB
4. Probability Distributions/3. Checking For Normal Distribution.mp412.8MB
4. Probability Distributions/4. Standard Normal Distribution and Z-scores.mp410MB
4. Probability Distributions/5. Confidence Interval-Theory.mp413.71MB
4. Probability Distributions/6. Confidence Interval-Computation in R.mp410.24MB
4. Probability Distributions/7. Conclusions to Section 4.mp43.39MB
5. Statistical Inference/1. What is Hypothesis Testing.mp413.41MB
5. Statistical Inference/2. T-tests Application in R.mp426.37MB
5. Statistical Inference/3. Non-Parametric Alternatives to T-Tests.mp413.02MB
5. Statistical Inference/4. One-way ANOVA.mp416.04MB
5. Statistical Inference/5. Non-parametric version of One-way ANOVA.mp45.9MB
5. Statistical Inference/6. Two-way ANOVA.mp414.21MB
5. Statistical Inference/7. Power Test for Detecting Effect.mp420.1MB
5. Statistical Inference/8. Conclusions to Section 5.mp45.46MB
6. Relationship Between Two Different Quantitative Variables/1. Explore the Relationship Between Two Quantitative Variables.mp49.43MB
6. Relationship Between Two Different Quantitative Variables/10. Analysis of Covariance (ANCOVA).mp417.52MB
6. Relationship Between Two Different Quantitative Variables/11. Selecting the Most Suitable Regression Model.mp433.28MB
6. Relationship Between Two Different Quantitative Variables/12. Conclusions to Section 6.mp45.39MB
6. Relationship Between Two Different Quantitative Variables/2. Correlation.mp443.4MB
6. Relationship Between Two Different Quantitative Variables/3. Linear Regression-Theory.mp424.87MB
6. Relationship Between Two Different Quantitative Variables/4. Linear Regression-Implementation in R.mp433.59MB
6. Relationship Between Two Different Quantitative Variables/5. The Conditions of Linear Regression.mp430.5MB
6. Relationship Between Two Different Quantitative Variables/6. Dealing with Multi-collinearity.mp438.17MB
6. Relationship Between Two Different Quantitative Variables/7. What More Does the Regression Model Tell Us.mp432.16MB
6. Relationship Between Two Different Quantitative Variables/8. Linear Regression and ANOVA.mp47.32MB
6. Relationship Between Two Different Quantitative Variables/9. Linear Regression With Categorical Variables and Interaction Terms.mp437.54MB
7. Other Types of Regression/1. Violation of Linear Regression Conditions Transform Variables.mp428.99MB
7. Other Types of Regression/10. Conclusions to Section 7.mp47.76MB
7. Other Types of Regression/2. Other Regression Techniques When Conditions of OLS Are Not Met.mp438.01MB
7. Other Types of Regression/3. Model 2 Regression Standardized Major Axis (SMA) Regression.mp428.33MB
7. Other Types of Regression/4. Polynomial and Non-linear regression.mp424.24MB
7. Other Types of Regression/5. Linear Mixed Effect Models.mp437.68MB
7. Other Types of Regression/6. Generalized Regression Model (GLM).mp411.83MB
7. Other Types of Regression/7. Logistic Regression in R.mp439.06MB
7. Other Types of Regression/8. Poisson Regression in R.mp414.13MB
7. Other Types of Regression/9. Goodness of fit testing.mp48.89MB
8. Multivariate Analysis/1. Why Do Multivariate Analysis.mp48MB
8. Multivariate Analysis/2. Cluster AnalysisUnsupervised Learning.mp434.93MB
8. Multivariate Analysis/3. Principal Component Analysis (PCA).mp429.72MB
8. Multivariate Analysis/4. Linear Discriminant Analysis (LDA).mp430.1MB
8. Multivariate Analysis/5. Correspondence Analysis.mp423.17MB
8. Multivariate Analysis/6. Similarity & Dissimilarity Across Sites.mp419.73MB
8. Multivariate Analysis/7. Non-metric multi dimensional scaling (NMDS).mp410.69MB
8. Multivariate Analysis/8. Multivariate Analysis of Variance (MANOVA).mp410.44MB
8. Multivariate Analysis/9. Conclusions to Section 8.mp46.22MB
9. Miscellaneous Lectures & Information/1. Exploratory Data Analysis With xda.mp410.91MB
9. Miscellaneous Lectures & Information/2. Read in Data from Online HTML Tables-Part 2.mp429.99MB