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文档列表

2. Section 2 The Essentials of the R Programming Language/7. Exploratory Data Analysis in R.mp4 50.6 MB
6. Relationship Between Two Different Quantitative Variables/2. Correlation.mp4 45.5 MB
2. Section 2 The Essentials of the R Programming Language/4. Reading in Data from Different Sources.mp4 44.7 MB
2. Section 2 The Essentials of the R Programming Language/6. Data Cleaning Removing Missing Values.mp4 42.5 MB
7. Other Types of Regression/7. Logistic Regression in R.mp4 41.0 MB
6. Relationship Between Two Different Quantitative Variables/6. Dealing with Multi-collinearity.mp4 40.0 MB
7. Other Types of Regression/2. Other Regression Techniques When Conditions of OLS Are Not Met.mp4 39.9 MB
7. Other Types of Regression/5. Linear Mixed Effect Models.mp4 39.5 MB
6. Relationship Between Two Different Quantitative Variables/9. Linear Regression With Categorical Variables and Interaction Terms.mp4 39.4 MB
3. Statistical Tools to Learn More About Your Data/5. Charting & Graphing Discrete Data.mp4 38.1 MB
8. Multivariate Analysis/2. Cluster AnalysisUnsupervised Learning.mp4 36.6 MB
6. Relationship Between Two Different Quantitative Variables/4. Linear Regression-Implementation in R.mp4 35.2 MB
6. Relationship Between Two Different Quantitative Variables/11. Selecting the Most Suitable Regression Model.mp4 34.9 MB
6. Relationship Between Two Different Quantitative Variables/7. What More Does the Regression Model Tell Us.mp4 33.7 MB
2. Section 2 The Essentials of the R Programming Language/3. Different Data Structures in R.mp4 32.0 MB
6. Relationship Between Two Different Quantitative Variables/5. The Conditions of Linear Regression.mp4 32.0 MB
8. Multivariate Analysis/4. Linear Discriminant Analysis (LDA).mp4 31.6 MB
9. Miscellaneous Lectures & Information/2. Read in Data from Online HTML Tables-Part 2.mp4 31.5 MB
8. Multivariate Analysis/3. Principal Component Analysis (PCA).mp4 31.2 MB
7. Other Types of Regression/1. Violation of Linear Regression Conditions Transform Variables.mp4 30.4 MB
1. Introduction to the Basics of Applied Statistical Modelling/1. Introduction to the Instructor and Course.mp4 30.1 MB
2. Section 2 The Essentials of the R Programming Language/5. Indexing and Subsetting of Data.mp4 29.9 MB
7. Other Types of Regression/3. Model 2 Regression Standardized Major Axis (SMA) Regression.mp4 29.7 MB
2. Section 2 The Essentials of the R Programming Language/2. Introduction to the R Statistical Software & R Studio.mp4 29.1 MB
5. Statistical Inference/2. T-tests Application in R.mp4 27.7 MB
1. Introduction to the Basics of Applied Statistical Modelling/3. Statistics in the Real World.mp4 26.5 MB
6. Relationship Between Two Different Quantitative Variables/3. Linear Regression-Theory.mp4 26.1 MB
7. Other Types of Regression/4. Polynomial and Non-linear regression.mp4 25.4 MB
8. Multivariate Analysis/5. Correspondence Analysis.mp4 24.3 MB
3. Statistical Tools to Learn More About Your Data/6. Deriving Insights from QualitativeNominal Data.mp4 22.2 MB
1. Introduction to the Basics of Applied Statistical Modelling/4. Designing Studies & Collecting Good Quality Data.mp4 21.9 MB
5. Statistical Inference/7. Power Test for Detecting Effect.mp4 21.1 MB
8. Multivariate Analysis/6. Similarity & Dissimilarity Across Sites.mp4 20.7 MB
3. Statistical Tools to Learn More About Your Data/4. Charting & Graphing Continuous Data.mp4 18.7 MB
6. Relationship Between Two Different Quantitative Variables/10. Analysis of Covariance (ANCOVA).mp4 18.4 MB
3. Statistical Tools to Learn More About Your Data/2. Measures of Center.mp4 17.8 MB
5. Statistical Inference/4. One-way ANOVA.mp4 16.8 MB
5. Statistical Inference/6. Two-way ANOVA.mp4 14.9 MB
7. Other Types of Regression/8. Poisson Regression in R.mp4 14.8 MB
4. Probability Distributions/5. Confidence Interval-Theory.mp4 14.4 MB
5. Statistical Inference/1. What is Hypothesis Testing.mp4 14.1 MB
5. Statistical Inference/3. Non-Parametric Alternatives to T-Tests.mp4 13.7 MB
4. Probability Distributions/3. Checking For Normal Distribution.mp4 13.4 MB
3. Statistical Tools to Learn More About Your Data/3. Measures of Variation.mp4 13.3 MB
7. Other Types of Regression/6. Generalized Regression Model (GLM).mp4 12.4 MB
9. Miscellaneous Lectures & Information/1. Exploratory Data Analysis With xda.mp4 11.4 MB
8. Multivariate Analysis/7. Non-metric multi dimensional scaling (NMDS).mp4 11.2 MB
8. Multivariate Analysis/8. Multivariate Analysis of Variance (MANOVA).mp4 10.9 MB
4. Probability Distributions/6. Confidence Interval-Computation in R.mp4 10.7 MB
4. Probability Distributions/4. Standard Normal Distribution and Z-scores.mp4 10.5 MB
4. Probability Distributions/2. Data Distribution Normal Distribution.mp4 10.1 MB
6. Relationship Between Two Different Quantitative Variables/1. Explore the Relationship Between Two Quantitative Variables.mp4 9.9 MB
1. Introduction to the Basics of Applied Statistical Modelling/5. Different Types of Data.mp4 9.8 MB
7. Other Types of Regression/9. Goodness of fit testing.mp4 9.3 MB
1. Introduction to the Basics of Applied Statistical Modelling/6. Conclusion to Section 1.mp4 9.0 MB
4. Probability Distributions/1. Background.mp4 8.8 MB
8. Multivariate Analysis/1. Why Do Multivariate Analysis.mp4 8.4 MB
7. Other Types of Regression/10. Conclusions to Section 7.mp4 8.1 MB
6. Relationship Between Two Different Quantitative Variables/8. Linear Regression and ANOVA.mp4 7.7 MB
8. Multivariate Analysis/9. Conclusions to Section 8.mp4 6.5 MB
5. Statistical Inference/5. Non-parametric version of One-way ANOVA.mp4 6.2 MB
5. Statistical Inference/8. Conclusions to Section 5.mp4 5.7 MB
2. Section 2 The Essentials of the R Programming Language/8. Conclusion to Section 2.mp4 5.7 MB
6. Relationship Between Two Different Quantitative Variables/12. Conclusions to Section 6.mp4 5.7 MB
3. Statistical Tools to Learn More About Your Data/7. Conclusions to Section 3.mp4 5.5 MB
4. Probability Distributions/7. Conclusions to Section 4.mp4 3.6 MB
1. Introduction to the Basics of Applied Statistical Modelling/2.1 Script4Lectures.zip.zip 114.3 kB
7. Other Types of Regression/3. Model 2 Regression Standardized Major Axis (SMA) Regression.mp4.jpg 83.7 kB
6. Relationship Between Two Different Quantitative Variables/2. Correlation.vtt 18.4 kB
2. Section 2 The Essentials of the R Programming Language/7. Exploratory Data Analysis in R.vtt 18.0 kB
6. Relationship Between Two Different Quantitative Variables/6. Dealing with Multi-collinearity.vtt 16.3 kB
7. Other Types of Regression/7. Logistic Regression in R.vtt 15.7 kB
2. Section 2 The Essentials of the R Programming Language/6. Data Cleaning Removing Missing Values.vtt 15.5 kB
6. Relationship Between Two Different Quantitative Variables/4. Linear Regression-Implementation in R.vtt 15.1 kB
6. Relationship Between Two Different Quantitative Variables/9. Linear Regression With Categorical Variables and Interaction Terms.vtt 14.7 kB
2. Section 2 The Essentials of the R Programming Language/4. Reading in Data from Different Sources.vtt 14.7 kB
7. Other Types of Regression/2. Other Regression Techniques When Conditions of OLS Are Not Met.vtt 14.4 kB
2. Section 2 The Essentials of the R Programming Language/3. Different Data Structures in R.vtt 13.9 kB
3. Statistical Tools to Learn More About Your Data/5. Charting & Graphing Discrete Data.vtt 13.8 kB
8. Multivariate Analysis/3. Principal Component Analysis (PCA).vtt 13.2 kB
6. Relationship Between Two Different Quantitative Variables/7. What More Does the Regression Model Tell Us.vtt 12.9 kB
8. Multivariate Analysis/2. Cluster AnalysisUnsupervised Learning.vtt 12.7 kB
6. Relationship Between Two Different Quantitative Variables/5. The Conditions of Linear Regression.vtt 12.6 kB
7. Other Types of Regression/5. Linear Mixed Effect Models.vtt 12.4 kB
6. Relationship Between Two Different Quantitative Variables/11. Selecting the Most Suitable Regression Model.vtt 12.2 kB
7. Other Types of Regression/1. Violation of Linear Regression Conditions Transform Variables.vtt 12.0 kB
8. Multivariate Analysis/4. Linear Discriminant Analysis (LDA).vtt 11.3 kB
2. Section 2 The Essentials of the R Programming Language/5. Indexing and Subsetting of Data.vtt 11.3 kB
5. Statistical Inference/2. T-tests Application in R.vtt 11.3 kB
2. Section 2 The Essentials of the R Programming Language/2. Introduction to the R Statistical Software & R Studio.vtt 11.1 kB
1. Introduction to the Basics of Applied Statistical Modelling/1. Introduction to the Instructor and Course.vtt 11.0 kB
7. Other Types of Regression/3. Model 2 Regression Standardized Major Axis (SMA) Regression.vtt 11.0 kB
6. Relationship Between Two Different Quantitative Variables/3. Linear Regression-Theory.vtt 10.1 kB
7. Other Types of Regression/4. Polynomial and Non-linear regression.vtt 9.9 kB
1. Introduction to the Basics of Applied Statistical Modelling/3. Statistics in the Real World.vtt 9.8 kB
1. Introduction to the Basics of Applied Statistical Modelling/4. Designing Studies & Collecting Good Quality Data.vtt 9.3 kB
8. Multivariate Analysis/5. Correspondence Analysis.vtt 9.0 kB
3. Statistical Tools to Learn More About Your Data/2. Measures of Center.vtt 8.2 kB
3. Statistical Tools to Learn More About Your Data/6. Deriving Insights from QualitativeNominal Data.vtt 8.0 kB
5. Statistical Inference/7. Power Test for Detecting Effect.vtt 7.9 kB
5. Statistical Inference/4. One-way ANOVA.vtt 7.3 kB
3. Statistical Tools to Learn More About Your Data/4. Charting & Graphing Continuous Data.vtt 7.2 kB
6. Relationship Between Two Different Quantitative Variables/10. Analysis of Covariance (ANCOVA).vtt 7.2 kB
8. Multivariate Analysis/6. Similarity & Dissimilarity Across Sites.vtt 7.1 kB
9. Miscellaneous Lectures & Information/2. Read in Data from Online HTML Tables-Part 2.vtt 6.9 kB
4. Probability Distributions/3. Checking For Normal Distribution.vtt 6.3 kB
7. Other Types of Regression/8. Poisson Regression in R.vtt 6.1 kB
4. Probability Distributions/5. Confidence Interval-Theory.vtt 6.0 kB
5. Statistical Inference/1. What is Hypothesis Testing.vtt 6.0 kB
3. Statistical Tools to Learn More About Your Data/3. Measures of Variation.vtt 5.9 kB
5. Statistical Inference/6. Two-way ANOVA.vtt 5.6 kB
5. Statistical Inference/3. Non-Parametric Alternatives to T-Tests.vtt 5.6 kB
7. Other Types of Regression/6. Generalized Regression Model (GLM).vtt 5.3 kB
4. Probability Distributions/6. Confidence Interval-Computation in R.vtt 4.8 kB
6. Relationship Between Two Different Quantitative Variables/1. Explore the Relationship Between Two Quantitative Variables.vtt 4.5 kB
4. Probability Distributions/4. Standard Normal Distribution and Z-scores.vtt 4.3 kB
8. Multivariate Analysis/8. Multivariate Analysis of Variance (MANOVA).vtt 4.3 kB
9. Miscellaneous Lectures & Information/1. Exploratory Data Analysis With xda.vtt 4.2 kB
8. Multivariate Analysis/7. Non-metric multi dimensional scaling (NMDS).vtt 4.1 kB
4. Probability Distributions/2. Data Distribution Normal Distribution.vtt 4.0 kB
7. Other Types of Regression/9. Goodness of fit testing.vtt 4.0 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 3.7 kB
7. Other Types of Regression/4.1 poly1.txt.txt 3.7 kB
6. Relationship Between Two Different Quantitative Variables/8. Linear Regression and ANOVA.vtt 3.6 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 2.8 kB
8. Multivariate Analysis/4.1 lda.txt.txt 2.8 kB
8. Multivariate Analysis/9. Conclusions to Section 8.vtt 2.7 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 2.5 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 2.4 kB
3. Statistical Tools to Learn More About Your Data/5.1 barplt1.txt.txt 2.4 kB
8. Multivariate Analysis/5.1 ca_r.txt.txt 2.4 kB
5. Statistical Inference/8. Conclusions to Section 5.vtt 2.4 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 2.1 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 1.9 kB
5. Statistical Inference/2.1 ttest1.txt.txt 1.9 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 1.6 kB
6. Relationship Between Two Different Quantitative Variables/2.1 Correlans.txt.txt 1.6 kB
4. Probability Distributions/7. Conclusions to Section 4.vtt 1.6 kB
2. Section 2 The Essentials of the R Programming Language/6.1 removeNAs.txt.txt 1.6 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 1.5 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 1.2 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 1.0 kB
6. Relationship Between Two Different Quantitative Variables/5.1 condns_regression1.txt.txt 1.0 kB
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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