[DesireCourse.Net] Udemy - Applied Statistical Modeling for Data Analysis in R

Creation Time	Feb. 21, 2023, 6:13 p.m.
Last Access Time	May 27, 2026, 3:11 a.m.
File Size	1.3 GB
Keywords	Applied for DesireCourse - Analysis Udemy R Statistical in Modeling Net Data
Total Requests	112
Total Files	185
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2. Section 2 The Essentials of the R Programming Language/7. Exploratory Data Analysis in R.mp4 48.2 MB
6. Relationship Between Two Different Quantitative Variables/2. Correlation.mp4 43.4 MB
2. Section 2 The Essentials of the R Programming Language/4. Reading in Data from Different Sources.mp4 42.6 MB
2. Section 2 The Essentials of the R Programming Language/6. Data Cleaning Removing Missing Values.mp4 40.5 MB
7. Other Types of Regression/7. Logistic Regression in R.mp4 39.1 MB
6. Relationship Between Two Different Quantitative Variables/6. Dealing with Multi-collinearity.mp4 38.2 MB
7. Other Types of Regression/2. Other Regression Techniques When Conditions of OLS Are Not Met.mp4 38.0 MB
7. Other Types of Regression/5. Linear Mixed Effect Models.mp4 37.7 MB
6. Relationship Between Two Different Quantitative Variables/9. Linear Regression With Categorical Variables and Interaction Terms.mp4 37.5 MB
3. Statistical Tools to Learn More About Your Data/5. Charting & Graphing Discrete Data.mp4 36.4 MB
8. Multivariate Analysis/2. Cluster AnalysisUnsupervised Learning.mp4 34.9 MB
6. Relationship Between Two Different Quantitative Variables/4. Linear Regression-Implementation in R.mp4 33.6 MB
6. Relationship Between Two Different Quantitative Variables/11. Selecting the Most Suitable Regression Model.mp4 33.3 MB
6. Relationship Between Two Different Quantitative Variables/7. What More Does the Regression Model Tell Us.mp4 32.2 MB
2. Section 2 The Essentials of the R Programming Language/3. Different Data Structures in R.mp4 30.5 MB
6. Relationship Between Two Different Quantitative Variables/5. The Conditions of Linear Regression.mp4 30.5 MB
8. Multivariate Analysis/4. Linear Discriminant Analysis (LDA).mp4 30.1 MB
9. Miscellaneous Lectures & Information/2. Read in Data from Online HTML Tables-Part 2.mp4 30.0 MB
8. Multivariate Analysis/3. Principal Component Analysis (PCA).mp4 29.7 MB
7. Other Types of Regression/1. Violation of Linear Regression Conditions Transform Variables.mp4 29.0 MB
1. Introduction to the Basics of Applied Statistical Modelling/1. Introduction to the Instructor and Course.mp4 28.7 MB
2. Section 2 The Essentials of the R Programming Language/5. Indexing and Subsetting of Data.mp4 28.5 MB
7. Other Types of Regression/3. Model 2 Regression Standardized Major Axis (SMA) Regression.mp4 28.3 MB
2. Section 2 The Essentials of the R Programming Language/2. Introduction to the R Statistical Software & R Studio.mp4 27.7 MB
5. Statistical Inference/2. T-tests Application in R.mp4 26.4 MB
1. Introduction to the Basics of Applied Statistical Modelling/3. Statistics in the Real World.mp4 25.3 MB
6. Relationship Between Two Different Quantitative Variables/3. Linear Regression-Theory.mp4 24.9 MB
7. Other Types of Regression/4. Polynomial and Non-linear regression.mp4 24.2 MB
8. Multivariate Analysis/5. Correspondence Analysis.mp4 23.2 MB
3. Statistical Tools to Learn More About Your Data/6. Deriving Insights from QualitativeNominal Data.mp4 21.1 MB
1. Introduction to the Basics of Applied Statistical Modelling/4. Designing Studies & Collecting Good Quality Data.mp4 20.9 MB
5. Statistical Inference/7. Power Test for Detecting Effect.mp4 20.1 MB
8. Multivariate Analysis/6. Similarity & Dissimilarity Across Sites.mp4 19.7 MB
3. Statistical Tools to Learn More About Your Data/4. Charting & Graphing Continuous Data.mp4 17.8 MB
6. Relationship Between Two Different Quantitative Variables/10. Analysis of Covariance (ANCOVA).mp4 17.5 MB
3. Statistical Tools to Learn More About Your Data/2. Measures of Center.mp4 17.0 MB
5. Statistical Inference/4. One-way ANOVA.mp4 16.0 MB
5. Statistical Inference/6. Two-way ANOVA.mp4 14.2 MB
7. Other Types of Regression/8. Poisson Regression in R.mp4 14.1 MB
4. Probability Distributions/5. Confidence Interval-Theory.mp4 13.7 MB
5. Statistical Inference/1. What is Hypothesis Testing.mp4 13.4 MB
5. Statistical Inference/3. Non-Parametric Alternatives to T-Tests.mp4 13.0 MB
4. Probability Distributions/3. Checking For Normal Distribution.mp4 12.8 MB
3. Statistical Tools to Learn More About Your Data/3. Measures of Variation.mp4 12.6 MB
7. Other Types of Regression/6. Generalized Regression Model (GLM).mp4 11.8 MB
9. Miscellaneous Lectures & Information/1. Exploratory Data Analysis With xda.mp4 10.9 MB
8. Multivariate Analysis/7. Non-metric multi dimensional scaling (NMDS).mp4 10.7 MB
8. Multivariate Analysis/8. Multivariate Analysis of Variance (MANOVA).mp4 10.4 MB
4. Probability Distributions/6. Confidence Interval-Computation in R.mp4 10.2 MB
4. Probability Distributions/4. Standard Normal Distribution and Z-scores.mp4 10.0 MB
4. Probability Distributions/2. Data Distribution Normal Distribution.mp4 9.6 MB
6. Relationship Between Two Different Quantitative Variables/1. Explore the Relationship Between Two Quantitative Variables.mp4 9.4 MB
1. Introduction to the Basics of Applied Statistical Modelling/5. Different Types of Data.mp4 9.4 MB
7. Other Types of Regression/9. Goodness of fit testing.mp4 8.9 MB
1. Introduction to the Basics of Applied Statistical Modelling/6. Conclusion to Section 1.mp4 8.5 MB
4. Probability Distributions/1. Background.mp4 8.4 MB
8. Multivariate Analysis/1. Why Do Multivariate Analysis.mp4 8.0 MB
7. Other Types of Regression/10. Conclusions to Section 7.mp4 7.8 MB
6. Relationship Between Two Different Quantitative Variables/8. Linear Regression and ANOVA.mp4 7.3 MB
8. Multivariate Analysis/9. Conclusions to Section 8.mp4 6.2 MB
5. Statistical Inference/5. Non-parametric version of One-way ANOVA.mp4 5.9 MB
5. Statistical Inference/8. Conclusions to Section 5.mp4 5.5 MB
2. Section 2 The Essentials of the R Programming Language/8. Conclusion to Section 2.mp4 5.4 MB
6. Relationship Between Two Different Quantitative Variables/12. Conclusions to Section 6.mp4 5.4 MB
3. Statistical Tools to Learn More About Your Data/7. Conclusions to Section 3.mp4 5.3 MB
4. Probability Distributions/7. Conclusions to Section 4.mp4 3.4 MB
1. Introduction to the Basics of Applied Statistical Modelling/2.1 Script4Lectures.zip.zip 111.6 KB
7. Other Types of Regression/3. Model 2 Regression Standardized Major Axis (SMA) Regression.mp4.jpg 81.8 KB
6. Relationship Between Two Different Quantitative Variables/2. Correlation.vtt 17.9 KB
2. Section 2 The Essentials of the R Programming Language/7. Exploratory Data Analysis in R.vtt 17.6 KB
6. Relationship Between Two Different Quantitative Variables/6. Dealing with Multi-collinearity.vtt 15.9 KB
7. Other Types of Regression/7. Logistic Regression in R.vtt 15.3 KB
2. Section 2 The Essentials of the R Programming Language/6. Data Cleaning Removing Missing Values.vtt 15.1 KB
6. Relationship Between Two Different Quantitative Variables/4. Linear Regression-Implementation in R.vtt 14.7 KB
6. Relationship Between Two Different Quantitative Variables/9. Linear Regression With Categorical Variables and Interaction Terms.vtt 14.4 KB
2. Section 2 The Essentials of the R Programming Language/4. Reading in Data from Different Sources.vtt 14.4 KB
7. Other Types of Regression/2. Other Regression Techniques When Conditions of OLS Are Not Met.vtt 14.1 KB
2. Section 2 The Essentials of the R Programming Language/3. Different Data Structures in R.vtt 13.6 KB
3. Statistical Tools to Learn More About Your Data/5. Charting & Graphing Discrete Data.vtt 13.5 KB
8. Multivariate Analysis/3. Principal Component Analysis (PCA).vtt 12.9 KB
6. Relationship Between Two Different Quantitative Variables/7. What More Does the Regression Model Tell Us.vtt 12.6 KB
8. Multivariate Analysis/2. Cluster AnalysisUnsupervised Learning.vtt 12.4 KB
6. Relationship Between Two Different Quantitative Variables/5. The Conditions of Linear Regression.vtt 12.3 KB
7. Other Types of Regression/5. Linear Mixed Effect Models.vtt 12.1 KB
6. Relationship Between Two Different Quantitative Variables/11. Selecting the Most Suitable Regression Model.vtt 12.0 KB
7. Other Types of Regression/1. Violation of Linear Regression Conditions Transform Variables.vtt 11.7 KB
8. Multivariate Analysis/4. Linear Discriminant Analysis (LDA).vtt 11.1 KB
2. Section 2 The Essentials of the R Programming Language/5. Indexing and Subsetting of Data.vtt 11.0 KB
5. Statistical Inference/2. T-tests Application in R.vtt 11.0 KB
2. Section 2 The Essentials of the R Programming Language/2. Introduction to the R Statistical Software & R Studio.vtt 10.8 KB
1. Introduction to the Basics of Applied Statistical Modelling/1. Introduction to the Instructor and Course.vtt 10.8 KB
7. Other Types of Regression/3. Model 2 Regression Standardized Major Axis (SMA) Regression.vtt 10.7 KB
6. Relationship Between Two Different Quantitative Variables/3. Linear Regression-Theory.vtt 9.8 KB
7. Other Types of Regression/4. Polynomial and Non-linear regression.vtt 9.6 KB
1. Introduction to the Basics of Applied Statistical Modelling/3. Statistics in the Real World.vtt 9.6 KB
1. Introduction to the Basics of Applied Statistical Modelling/4. Designing Studies & Collecting Good Quality Data.vtt 9.1 KB
8. Multivariate Analysis/5. Correspondence Analysis.vtt 8.8 KB
3. Statistical Tools to Learn More About Your Data/2. Measures of Center.vtt 8.0 KB
3. Statistical Tools to Learn More About Your Data/6. Deriving Insights from QualitativeNominal Data.vtt 7.8 KB
5. Statistical Inference/7. Power Test for Detecting Effect.vtt 7.7 KB
5. Statistical Inference/4. One-way ANOVA.vtt 7.1 KB
3. Statistical Tools to Learn More About Your Data/4. Charting & Graphing Continuous Data.vtt 7.0 KB
6. Relationship Between Two Different Quantitative Variables/10. Analysis of Covariance (ANCOVA).vtt 7.0 KB
8. Multivariate Analysis/6. Similarity & Dissimilarity Across Sites.vtt 6.9 KB
9. Miscellaneous Lectures & Information/2. Read in Data from Online HTML Tables-Part 2.vtt 6.7 KB
4. Probability Distributions/3. Checking For Normal Distribution.vtt 6.1 KB
7. Other Types of Regression/8. Poisson Regression in R.vtt 5.9 KB
4. Probability Distributions/5. Confidence Interval-Theory.vtt 5.9 KB
5. Statistical Inference/1. What is Hypothesis Testing.vtt 5.8 KB
3. Statistical Tools to Learn More About Your Data/3. Measures of Variation.vtt 5.7 KB
5. Statistical Inference/6. Two-way ANOVA.vtt 5.5 KB
5. Statistical Inference/3. Non-Parametric Alternatives to T-Tests.vtt 5.5 KB
7. Other Types of Regression/6. Generalized Regression Model (GLM).vtt 5.2 KB
4. Probability Distributions/6. Confidence Interval-Computation in R.vtt 4.7 KB
6. Relationship Between Two Different Quantitative Variables/1. Explore the Relationship Between Two Quantitative Variables.vtt 4.4 KB
4. Probability Distributions/4. Standard Normal Distribution and Z-scores.vtt 4.2 KB
8. Multivariate Analysis/8. Multivariate Analysis of Variance (MANOVA).vtt 4.2 KB
9. Miscellaneous Lectures & Information/1. Exploratory Data Analysis With xda.vtt 4.1 KB
8. Multivariate Analysis/7. Non-metric multi dimensional scaling (NMDS).vtt 4.0 KB
4. Probability Distributions/2. Data Distribution Normal Distribution.vtt 3.9 KB
7. Other Types of Regression/9. Goodness of fit testing.vtt 3.9 KB
1. Introduction to the Basics of Applied Statistical Modelling/5. Different Types of Data.vtt 3.7 KB
1. Introduction to the Basics of Applied Statistical Modelling/6. Conclusion to Section 1.vtt 3.6 KB
7. Other Types of Regression/4.1 poly1.txt.txt 3.6 KB
6. Relationship Between Two Different Quantitative Variables/8. Linear Regression and ANOVA.vtt 3.5 KB
4. Probability Distributions/1. Background.vtt 3.4 KB
8. Multivariate Analysis/1. Why Do Multivariate Analysis.vtt 3.3 KB
7. Other Types of Regression/10. Conclusions to Section 7.vtt 3.3 KB
2. Section 2 The Essentials of the R Programming Language/7.1 EDA.txt.txt 2.7 KB
8. Multivariate Analysis/4.1 lda.txt.txt 2.7 KB
8. Multivariate Analysis/9. Conclusions to Section 8.vtt 2.6 KB
7. Other Types of Regression/5.1 linMix.txt.txt 2.5 KB
2. Section 2 The Essentials of the R Programming Language/8. Conclusion to Section 2.vtt 2.4 KB
6. Relationship Between Two Different Quantitative Variables/12. Conclusions to Section 6.vtt 2.4 KB
7. Other Types of Regression/7.1 logisticreg1.txt.txt 2.3 KB
3. Statistical Tools to Learn More About Your Data/5.1 barplt1.txt.txt 2.3 KB
8. Multivariate Analysis/5.1 ca_r.txt.txt 2.3 KB
5. Statistical Inference/8. Conclusions to Section 5.vtt 2.3 KB
5. Statistical Inference/5. Non-parametric version of One-way ANOVA.vtt 2.3 KB
7. Other Types of Regression/2.1 Lecture50_others regs1.txt.txt 2.1 KB
3. Statistical Tools to Learn More About Your Data/7. Conclusions to Section 3.vtt 2.0 KB
5. Statistical Inference/6.1 2wayAn1.txt.txt 1.9 KB
7. Other Types of Regression/1.1 Lecture49_transform.txt.txt 1.9 KB
8. Multivariate Analysis/2.1 cluster1.txt.txt 1.8 KB
5. Statistical Inference/2.1 ttest1.txt.txt 1.8 KB
6. Relationship Between Two Different Quantitative Variables/6.1 multicol1.txt.txt 1.8 KB
6. Relationship Between Two Different Quantitative Variables/9.1 intercnreg.txt.txt 1.5 KB
6. Relationship Between Two Different Quantitative Variables/2.1 Correlans.txt.txt 1.5 KB
4. Probability Distributions/7. Conclusions to Section 4.vtt 1.5 KB
2. Section 2 The Essentials of the R Programming Language/6.1 removeNAs.txt.txt 1.5 KB
6. Relationship Between Two Different Quantitative Variables/10.1 ancova1.txt.txt 1.5 KB
6. Relationship Between Two Different Quantitative Variables/7.1 more_lin reg1.txt.txt 1.5 KB
8. Multivariate Analysis/3.1 pca_r.txt.txt 1.5 KB
7. Other Types of Regression/3.1 sma1.txt.txt 1.5 KB
2. Section 2 The Essentials of the R Programming Language/4.1 read_inExternalData.txt.txt 1.4 KB
3. Statistical Tools to Learn More About Your Data/6.1 chisq1.txt.txt 1.4 KB
5. Statistical Inference/4.1 oneAnova1.txt.txt 1.3 KB
2. Section 2 The Essentials of the R Programming Language/1. Rationale for this section.html 1.3 KB
3. Statistical Tools to Learn More About Your Data/4.1 boxplt1.txt.txt 1.3 KB
7. Other Types of Regression/8.1 poisson1.txt.txt 1.2 KB
6. Relationship Between Two Different Quantitative Variables/11.1 model_selcn.txt.txt 1.1 KB
9. Miscellaneous Lectures & Information/1.1 xda.txt.txt 1.1 KB
2. Section 2 The Essentials of the R Programming Language/5.1 indexingDF.txt.txt 1014 bytes
6. Relationship Between Two Different Quantitative Variables/5.1 condns_regression1.txt.txt 1002 bytes
5. Statistical Inference/3.1 mann_wil1.txt.txt 912 bytes
3. Statistical Tools to Learn More About Your Data/2.1 meanData.txt.txt 879 bytes
9. Miscellaneous Lectures & Information/2.1 readHTML_rcurl.txt.txt 843 bytes
8. Multivariate Analysis/7.1 nmds1.txt.txt 839 bytes
8. Multivariate Analysis/8.1 manova1.txt.txt 794 bytes
6. Relationship Between Two Different Quantitative Variables/4.1 regression1.txt.txt 717 bytes
4. Probability Distributions/6.1 CIinR1.txt.txt 639 bytes
3. Statistical Tools to Learn More About Your Data/1. Summarize Quantitative Data.html 529 bytes
5. Statistical Inference/5.1 nonP_krusk1.txt.txt 480 bytes
1. Introduction to the Basics of Applied Statistical Modelling/2. Data & Code Used in the Course.html 455 bytes
4. Probability Distributions/3.1 checkNorm.txt.txt 411 bytes
3. Statistical Tools to Learn More About Your Data/3.1 sd_se1.txt.txt 308 bytes
2. Section 2 The Essentials of the R Programming Language/9. Section 2 Quiz.html 161 bytes
3. Statistical Tools to Learn More About Your Data/8. Section 3 Quiz.html 161 bytes
4. Probability Distributions/8. Section 4 Quiz.html 161 bytes
5. Statistical Inference/9. Section 5 Quiz.html 161 bytes
6. Relationship Between Two Different Quantitative Variables/13. Section 6 Quiz.html 161 bytes
7. Other Types of Regression/11. Section 7 Quiz.html 161 bytes
8. Multivariate Analysis/10. Section 8 Quiz.html 161 bytes
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[DesireCourse.Net] Udemy - Applied Statistical Modeling for Data Analysis in R

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