Reading 11-Sampling and Estimation

msk2222's version from 2018-02-18 23:13




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Definition of Simple Random SampleA simple random sample is a subset of a larger population created in such a way that each element of the population has an equal probability of being selected to the subset.
systematic samplingevery kth member until we have a sample of the desired size.
Definition of Sampling Error.Sampling error is the difference between the observed value of a statistic and the quantity it is intended to estimate.
Definition of Sampling Distribution of a StatisticThe sampling distribution of a statistic is the distribution of all the distinct possible values that the statistic can assume when computed from samples of the same size randomly drawn from the same population.
Definition of Stratified Random Sampling the population is divided into subpopulations (strata) based on one or more classification criteria. Simple random samples are then drawn from each stratum in sizes proportional to the relative size of each stratum in the population. These samples are then pooled to form a stratified random sample.
IndexingAn investment strategy in which an investor constructs a portfolio to mirror the performance of a specified index
time seriesa sequence of returns collected at discrete and equally spaced intervals of time (such as a historical series of monthly stock returns)
Cross-sectional datadata on some characteristic of individuals, groups, geographical regions, or companies at a single point in time.
monetary policyActions taken by a nation’s central bank to affect aggregate output and prices through changes in bank reserves, reserve requirements, or its target interest rate


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Central Limit TheoremGiven a population described by any probability distribution having mean μ and finite variance σ2, the sampling distribution of the sample mean X, computed from samples of size n from this population will be approximately normal with mean μ (the population mean) and variance σ2/n (the population variance divided by n) when the sample size n is large.
Definition of the Standard Error of the Sample Mean sample mean X calculated from a sample generated by a population with standard deviation σ, the standard error of the sample mean is given by one of two expressions
The distribution of the sample meanwill be approximately normal.
The mean of the distribution ofwill be equal to the mean of the population from which the samples are drawn.
The variance of the distribution ofwill be equal to the variance of the population divided by the sample size.


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estimators formulas that we use to compute the sample mean and all the other sample statistics are examples of estimation formulas
estimate.particular value that we calculate from sample observations using an estimator
point estimate of the population meanthe calculated value of the sample mean in a given sample, used as an estimate of the population mean
Definition of Confidence IntervalA confidence interval is a range for which one can assert with a given probability 1 − α, called the degree of confidence, that it will contain the parameter it is intended to estimate. This interval is often referred to as the 100(1 − α)% confidence interval for the parameter.
t-distributionsymmetrical probability distribution defined by a single parameter known as degrees of freedom (df). Each value for the number of degrees of freedom defines one distribution in this family of distributions.


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Data miningoveruse of the same or related data in ways that we shall describe shortly. Data-mining bias refers to the errors that arise from such misuse of data
Out-of-sample testA test of a strategy or model using a sample outside the time period on which the strategy or model was developed.
Intergenerational data mining using information developed by previous researchers using a dataset to guide current research using the same or a related dataset.
look-ahead bias uses information that was not available on the test date. For example, tests of trading rules that use stock market returns and accounting balance sheet data must account for look-ahead bias.
Time-Period Bias.A test design is subject to time-period bias if it is based on a time period that may make the results time-period specific