05 Jan Exploratory Data Analysis – Central tendency
In this series of posts, we will make a brief introduction in one-sample parametric test using the student t-test statistical test. ...
Statistical Concepts in Real Estate
14 Mar Two Sample t-Test
In this series of posts, we will make a brief introduction in one-sample parametric test using the student t-test statistical test. ...
13 Mar One Sample Statistical Test
In this series of posts, we will make a brief introduction in one-sample parametric test using the student t-test statistical test. ...
25 Feb Pearson and Spearman Correlations in R
In this post we will use a practical example using R to caclulate Spearman and Pearson correlations....
21 Feb Pearson and Spearman Correlations
In this post we will learn about some important correlation coefficients, essential for exploratory data analysis and model building....
16 Feb Measuring execution time in R
Execution time is essential in modern data analysis. Due to the vast amount of available data, minimizing execution time can be highly beneficial in large scale projects where delivery time and proper evaluation is of utmost importance....
05 Feb Beyond Linear Modeling using R (part-2)
Non-linear relationships are equally important to linear ones and in this post we will showcase an another basic approach in modeling exponential relationships between a predictor variable and a response variable. ...
03 Feb Beyond Linear Modeling using R (part-1)
Non-linear relationships are equally important to linear ones and in this post we will showcase a basic approach in case of exponential relationship between a predictor variable and a response variable. ...
20 Jan Linear Regression Modeling with R
Having discussed about the mathematical formulation and assumptions of the linear regression, its time to do some modeling using some specialised functions in R....
17 Jan Linear Regression Summary Statistics
Summary statistics returned by the lm() object in R, highlight some important measurements used to decide the overall fitting performance of the linear model to our dataset....