2 edition of An estimate of basic demographic parameters for Indonesia found in the catalog.
An estimate of basic demographic parameters for Indonesia
Includes bibliographical references.
|Statement||by N. Iskandar.|
|LC Classifications||HA1816 .I8|
|The Physical Object|
|Number of Pages||42|
|LC Control Number||70941396|
- The “population of India on April 1, ," - The "population of American black females in the Northeast on June 1, ” 2. Kind of collectivity that persists through time even though its members are continuously changing through attrition and accession. Thus, "the population of India" may refer to the aggregate of persons who have. Occasion-specific population estimates were added as a derived parameter to the immigration-emigration mark-resight estimator. April, The ability to recompute real and derived parameter estimates in the Results Browser without re-optimizing the model was added.
The total population presents one overall measure of the potential impact of the country on the world and within its region. Note: Starting with the Factbook, demographic estimates for some countries (mostly African) have explicitly taken into account t more. employment from each sample and use it as an estimate of the population average. It is clear from Table , that the sample estimates lie within the range of 11 to Some samples give a very low figure while some others give a high estimate. But the average of all the sample estimates is 27, which is the true average of the population.
Analysis of demographic variables is much easier when specific questions on births, deaths and migration are asked in the data sources. This section focuses on the link between understanding and utilizing available demographic data sources in Indonesia to estimate demographic parameters, with special attention to three data sources: the. With the estimate of bias in hand, an obvious extension is to de ne a Jackknife estimate of the parameter of interest as ^ jack= ^ biasd jack= ^ (n 1)(^ () ^) = n ^ (n 1) ^ The estimator is made clear if we remember than the Jackknife bias of the original estimator is (n 1)(^ (jack) ^), and hence the bias of the new estimator ^ is 0.
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In statistics, sampling errors are incurred when the statistical characteristics of a population are estimated from a subset, or sample, of that population. Since the sample does not include all members of the population, statistics on the sample, such as means and quartiles, generally differ from the characteristics of the entire population.
An unbiased estimator of a population parameter is an estimator whose expected value is equal to that pa-rameter. Formally, an estimator ˆµ for parameter µ is said to be unbiased if: E(ˆµ) = µ.
(1) Example: The sample mean X¯ is an unbiased estimator for the population mean µ. Statistics - Statistics - Estimation of a population mean: The most fundamental point and interval estimation process involves the estimation of a population mean.
Suppose it is of interest to estimate the population mean, μ, for a quantitative variable. Data collected from a simple random sample can be used to compute the sample mean, x̄, where the value of x̄ provides a point estimate.
There are two ways to learn about a population parameter. 1) We can use confidence intervals to estimate parameters. "We can be 95% confident that the proportion of Penn State students who have a tattoo is between % and %." 2) We can use hypothesis tests to test and ultimately draw conclusions about the value of a parameter.
Definition and basic properties. The MSE assesses the quality of a predictor (i.e., a function mapping arbitrary inputs to a sample of values of some random variable), or an estimator (i.e., a mathematical function mapping a sample of data to an estimate of a parameter of the population from which the data is sampled).
The definition of an MSE differs according. The statistic is an estimate of a population parameter. A parameter is a number that is a property of the population. Since we considered all math classes to be the population, then the average number of points earned per student over all the math classes is an example of a parameter.
Population: all math classes. Sample: One of the math classes. Defining a population. A sample is a concrete thing. You can open up a data file, and there’s the data from your sample. A population, on the other hand, is a more abstract refers to the set of all possible people, or all possible observations, that you want to draw conclusions about, and is generally much bigger than the sample.
In an ideal world, the. Page (C:\Users\B. Burt Gerstman\Dropbox\StatPrimer\, 5/8/). Statistical inference. Statistical inference is the act of generalizing from the data (“sample”) to a larger phenomenon (“population”) with calculated degree of certainty.
The act of generalizing and deriving statistical judgments is the process of inference.[Note: There is a distinction. accounting for the ecological, demographic, or habitat-related factors that affect sampling efficiency will produce the most reliable estimates of fish population parameters.
Understanding bias and precision becomes particularly important when determining whether to estimate population parameters directly or to estimate population parameters in. Maximum-likelihood methods have a natural interpretation in terms of best linear unbiased predictors.
Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill.
Statistical Inference, Model & Estimation. Recall, a statistical inference aims at learning characteristics of the population from a sample; the population characteristics are parameters and sample characteristics are statistics.
A statistical model is a representation of a complex phenomena that generated the data. It has mathematical formulations that describe.
It is a common requirement to efficiently estimate population parameters based on simple random sample data. In the R tutorials of this section, we demonstrate how to compute the estimates.
The steps are to be illustrated with a built-in data frame named survey. the United States (the population), watch TV.
The mean we measure for these 20 children is a sample mean. We can then compare the sample mean we select to the population mean stated in the article. Hypothesis testing or significance testing is a method for testing a claim or hypothesis about a parameter in a population, using data measured in a.
Population Parameters A parameter is data based on an entire population. Statistics such as averages and standard deviations, when taken from populations, are referred to as population parameters.
You could estimate many population parameters with sample data, but here you calculate the most popular statistics: mean, variance, standard deviation, covariance, and correlation. The following list indicates how each parameter and its corresponding estimator is calculated. Mean (average): The mean is the simple average of the random variable, X.
Let’s consider the example from earlier, where we want to estimate the percentage of library members who read the latest novel from J. Rowling. However, let’s suppose that of our sample of size members, 15 members already purchased the new book by J.
Rowling. This gives a point estimate of 15%, or for the population parameter. The first comprehensive demographic study of Indonesia, this book makes an important contribution to the understanding of the political and economic problems - both past and present - of the world's fourth most populous country.
It demonstrates that the period to will be particularly crucial for Indonesia and will require careful social and economic planning. A population is defined as the set of all individuals, items, or data of interest. This is the group about which scientists will generalize.
A characteristic (usually numeric) that describes a population is referred to as a population parameter. The alternative is to select a portion or sample of individuals in the popula - tion. A distinction is made between an estimate and an estimator. The numerical value of the sample mean is said to be an estimate of the population mean figure.
On the other hand, the statistical measure used, that is, the method of estimation is referred to as an estimator, Properties of Good Estimator assignment help, Properties of Good Estimator homework help, estimator is. And that has huge implications for the global book industry.
India is currently the world’s second-most populous country with over billion people. And population growth forecasts estimate that India will surpass the most populous country today, China, by the end ofwith a population of some billion.
A parameter is a value describing a characteristic of a population. In a statistical study the value of a parameter is typically unknown. All currently registered students at a particular college form a population. Two population characteristics of interest could be the average GPA and the proportion of students over \(23\) years.
Population.The Bayesian approach estimates pharmacokinetic parameters (e.g., k el and Vd) that will be most consistent with serum levels predicted by both the population model and the actual measured serum levels. To achieve that end, the least squares method based on the Bayesian algorithm estimates the parameters which minimize the following function.The population of Indonesia was million according to the national census, and it was estimated to reach million in Fifty-eight per cent live on the island of Java, the world's most populous island.
Despite a fairly effective family planning program that has been in place sinceIndonesia's population growth was % for the decade ending in