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# noc21_ma36 - Lecture 03

### noc21-ma36-lec50

In this lecture, the ordinary least squares estimator for multiple linear regression model is discussed using R commands. Matrix plot and correlation plot is also illustrated.

### noc21-ma36-lec45

In this lecture, properties of the direct regression estimators and model fitting using R is discussed with examples for simple linear regression.

### noc21-ma36-lec41

In this lecture, simple linear regression model and estimation of parameters using least squares method is discussed with examples.

### noc21_ma36 - Lecture 48

In this lecture, some basic concepts regarding multiple linear regression is discussed with examples.

### noc21-ma36-lec47

In this lecture, testing of hypothesis and confidence interval estmation is discussed for simple linear regression using R commands.

### noc21-ma36-lec03

1. This lecture discusses how to assign values to variables in R.
2. Also we will learn how R can be used as a calculator for doing basic mathematical calculations.1. This lecture discusses how to assign values to variables in R.
2. Also we will learn how R can be used as a calculator for doing basic mathematical calculations.

### noc21-ma36-lec05

This lecture talks about how different basic operations can be used on a vector. It includes finding maximum, minimum, square root, absolute values and so on. Even, if some elements are missing in a vector, we can handle it in R.

### noc21-ma36-lec53

In this lecture, test of significance of regression (Analysis of variance) is discussed with examples and implementation using R commands.

### noc21-ma36-lec46

In this lecture, maximum likelihood estimators of regression coefficients and it's properties are discussed. Testing of hypothesis and confidence interval estmation is also discussed for simple linear regression.

### noc21-ma36-lec44

In this lecture, fitting linear models with R software is discussed with examples and corresponding R commands.

### noc21-ma36-lec04

1. In this lecture, different operations on data vectors in R is discussed in detail.
2. It includes power operations, addition, subtraction, multiplication and so on.1. In this lecture, different operations on data vectors in R is discussed in detail.
2. It includes power operations, addition, subtraction, multiplication and so on.

### noc21-ma36-lec18

In this lecture, simple random sampling is discussed using R software with the packages sampling and sample.

### noc21-ma36-lec19

In this lecture, estimation of population mean is discussed. Unbiasedness of sample mean under SRSWOR and SRSWR is also discussed.

### noc21-ma36-lec06

In this lecture, some basic operations on matrices like addition, subtraction, multiplication are discussed in detail. Extracting a submatrix from a large matrix is also addressed.

### noc21-ma36-lec15

In this lecture, probabilities of selection os samples in case of SRSWOR and SRSWR is discussed with mathematical details.

### noc21-ma36-lec52

In this lecture, test of hypothesis on individual regression coefficients is discussed with examples and R commands. Model fitting with R and confidence interval on individual regression coefficient is also discussed.

### noc21-ma36-lec16

In this lecture, SRSWOR and SRSWR is discussed in R software using the R package sample.