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R

Data Analysis and Predictive Modeling in R

260

Statinfer

₹3,999

Course Currilcum

    • Handout – Introduction to R 00:00:00
    • 1.1 Getting Started in R FREE 00:00:00
    • 1.2 R Environment FREE 00:00:00
    • 1.3 R Packages 00:00:00
    • 1.4 R Data Types Vectors 00:00:00
    • 1.5 R Dataframes 00:00:00
    • 1.6 List in R 00:00:00
    • 1.7 Factor and Matrices 00:00:00
    • 1.8 R History and Scripts 00:00:00
    • 1.9 R Functions 00:00:00
    • 1.10 Errors in R 00:00:00
    • R quiz unit 1 Unlimited
    • Handout – Data Handling in R 00:00:00
    • 2.1 Data handling introduction FREE 00:00:00
    • 2.2 Importing the Datasets FREE 00:00:00
    • 2.3 Checklist 00:00:00
    • 2.4 Subsetting the Data 00:00:00
    • 2.5 Subsetting Variable Condition 00:00:00
    • 2.6 Calculated Fields _ ifelse 00:00:00
    • 2.7 Sorting and Duplicates 00:00:00
    • 2.8 Joining and Merging 00:00:00
    • 2.9 Exporting the Data 00:00:00
    • R Quiz Unit 2 Unlimited
    • Handout – Basic Statistics, Plots and Reporting in R 00:00:00
    • 3.1 Introduction and Sampling FREE 00:00:00
    • 3.2 Descriptive Statistics FREE 00:00:00
    • 3.3 Percentiles and Quartiles 00:00:00
    • 3.4 Box Plots 00:00:00
    • 3.5 Creating Graphs and Conclusion 00:00:00
    • R Quiz Unit 3 Unlimited
    • Handout – Regression Analysis 00:00:00
    • 1.1 Introduction and Corelation FREE 00:00:00
    • 1.2 LAB Corelation Calculation in R FREE 00:00:00
    • 1.3 Beyond Pearson Corelation 00:00:00
    • 1.4 From Corelation to Regression 00:00:00
    • 1.5 Regression Line Fitting in R 00:00:00
    • 1.6 R Squared 00:00:00
    • 1.7 Multiple Regression 00:00:00
    • 1.8 Adjusted R Squared 00:00:00
    • 1.9 Issue with Multiple Regression 00:00:00
    • 1.10 Multicollinearity 00:00:00
    • 1.11 Regression Conclusion 00:00:00
    • Regression Quiz Unlimited
    • Handout – Logistic Regression in R 00:00:00
    • 2.1 Need of Non-Linear Regression FREE 00:00:00
    • 2.2 Logistic Function and Line FREE 00:00:00
    • 2.3 Multiple Logistic Regression 00:00:00
    • 2.4 Goodness of Fit for a Logistic Regression 00:00:00
    • 2.5 Multicollinearity in Logistic Regression in R 00:00:00
    • 2.6 Individual Impact of Variables in R 00:00:00
    • 2.7 Model Selection in R 00:00:00
    • 2.8 Logistic Regression Conclusion 00:00:00
    • Logistic Regression Quiz Unlimited
    • Handout – Model Selection and Cross Validation in R 00:00:00
    • 4.1 Introduction to Model Selection FREE 00:00:00
    • 4.2 Sensitivity Specificity FREE 00:00:00
    • 4.3 Sensitivity Specificity Continued 00:00:00
    • 4.4 ROC AUC 00:00:00
    • 4.5 The Best Model 00:00:00
    • 4.6 Errors 00:00:00
    • 4.7 Overfitting Underfitting 00:00:00
    • 4.8 Bias_Variance Treadoff 00:00:00
    • 4.9 Holdout Data Validation 00:00:00
    • 4.10 Ten Fold CV 00:00:00
    • 00:00:00
    • Direct Mail Marketing 00:00:00
    • Automobile Pricing Strategy 00:00:00
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