NOC:Descriptive Statistics with R Software


Lecture 1 - Introduction to R Software


Lecture 2 - Basics and R as a Calculator


Lecture 3 - Calculations with Data Vectors


Lecture 4 - Built-in Commands and Missing Data Handling


Lecture 5 - Operations with Matrices


Lecture 6 - Objectives, Steps and Basic Definitions


Lecture 7 - Variables and Types of Data


Lecture 8 - Absolute Frequency, Relative Frequency and Frequency Distribution


Lecture 9 - Frequency Distribution and Cumulative Distribution Function


Lecture 10 - Bar Diagrams


Lecture 11 - Subdivided Bar Plots and Pie Diagrams


Lecture 12 - 3D Pie Diagram and Histogram


Lecture 13 - Kernel Density and Stem - Leaf Plots


Lecture 14 - Arithmetic Mean


Lecture 15 - Median


Lecture 16 - Quantiles


Lecture 17 - Mode, Geometric Mean and Harmonic Mean


Lecture 18 - Range, Interquartile Range and Quartile Deviation


Lecture 19 - Absolute Deviation and Absolute Mean Deviation


Lecture 20 - Mean Squared Error, Variance and Standard Deviation


Lecture 21 - Coefficient of Variation and Boxplots


Lecture 22 - Raw and Central Moments


Lecture 23 - Sheppard's Correction, Absolute Moments and Computation of Moments


Lecture 24 - Skewness and Kurtosis


Lecture 25 - Univariate and Bivariate Scatter Plots


Lecture 26 - Smooth Scatter Plots


Lecture 27 - Quantile- Quantile and Three Dimensional Plots


Lecture 28 - Correlation Coefficient


Lecture 29 - Correlation Coefficient Using R Software


Lecture 30 - Rank Correlation Coefficient


Lecture 31 - Measures of Association for Discrete and Counting Variables - Part 1


Lecture 32 - Measures of Association for Discrete and Counting Variables - Part 2


Lecture 33 - Least Squares Method - One Variable


Lecture 34 - Least Squares Method - R Commands and More than One Variables