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2. 6 ways to get the lowest rate on your next mortgage - AOL

   www.aol.com/finance/how-to-get-best-mortgage...

   6. Do the math before buying points. Some lenders give you the option to buy "points" in order to reduce your interest rate. One point typically costs 1% of your loan amount.

3. How to read and compare mortgage loan estimates - AOL

   www.aol.com/finance/read-compare-mortgage-loan...

   The final page of the loan estimate lists more important details of your mortgage agreement, like the names of the lender and the loan officer, plus three key figures you can use for comparison ...

4. Minimum-variance unbiased estimator - Wikipedia

   en.wikipedia.org/wiki/Minimum-variance_unbiased...

   However, the sample standard deviation is not unbiased for the population standard deviation – see unbiased estimation of standard deviation. Further, for other distributions the sample mean and sample variance are not in general MVUEs – for a uniform distribution with unknown upper and lower bounds, the mid-range is the MVUE for the ...

5. The best home loan: how to shop for and compare mortgage offers

   www.aol.com/finance/best-home-loan-shop-compare...

   Even an interest rate savings of as little as 0.1 percent, for instance, can result in thousands of dollars remaining in your pocket over the life of a mortgage, according to Bankrate’s mortgage ...

6. Mortgage calculator - Wikipedia

   en.wikipedia.org/wiki/Mortgage_calculator

   Mortgage calculators are frequently on for-profit websites, though the Consumer Financial Protection Bureau has launched its own public mortgage calculator. [ 3 ] : 1267, 1281–83 The major variables in a mortgage calculation include loan principal, balance, periodic compound interest rate, number of payments per year, total number of payments ...

7. Point estimation - Wikipedia

   en.wikipedia.org/wiki/Point_estimation

   , X n, the estimator T is called an unbiased estimator for the parameter θ if E[T] = θ, irrespective of the value of θ. [1] For example, from the same random sample we have E(x̄) = μ (mean) and E(s 2) = σ 2 (variance), then x̄ and s 2 would be unbiased estimators for μ and σ 2. The difference E[T ] − θ is called the bias of T ; if ...