### Sampling & Survey # 9 – Regression Estimation

Today, we shall look at regression estimation. We will begin by looking at the usual & simple straight line regression model: . Let and by the ordinary least squares (OLS) regression [...]

Today, we shall look at regression estimation. We will begin by looking at the usual & simple straight line regression model: . Let and by the ordinary least squares (OLS) regression [...]

So last time we saw STR and here is a quick recap. Set the stratification scheme Set the stratum design Implement the sampling methods for each stratum independently Pool the strum estimates to [...]

SRS form the basis of sampling and survey methods as it is easy to design and analyse, but it is rarely the best design. We may adopt systematic sampling or cluster sampling but we often are [...]

For today, it is going to be a short and simple session on Systematic Sampling, We can effectively consider systematic sampling as a proxy for simple random sampling. We start by taking (rounding [...]

So let us now continue study SRS. Recall in part 3, we introduced the idea of unit inclusion probability. Subsequently, we introduced , which is the sampling weight. The sampling weight of unit i [...]

So we formally introduced the estimators used in SRS previously. Now, we are interested in how good our estimators are, and if you recall, by good, I refer to accuracy (MSE), Precision (Variance) [...]

Today we shall look at the first sampling method we introduced: Simple Random Sampling. Recall that we mentioned that this is the most basic form of probability sampling since it provides the [...]

So recall that we are interested on the statistical aspects of taking and analysing a sample, and a good sample will be representative in the sense that characteristics of interest in the [...]

This is a new series (this is essentially post-graduate materials, meaning you need strong statistical background at university level) on Sampling and Survey. I know many JC students will think, [...]

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