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What sample statistic is used to estimate a population parameter?
A point estimate is a single value (statistic) used to estimate a population value (parameter)true apex
What is the absolute value of the difference between the point estimate and the population parameter it estimates?
B. The sampling error
A parameter is a numerical descriptor that is used to describe a population or a sample?
Either.
Is a single number characteristic describe a population is called a parameter?
Parameter
What is the difference between statistics and parameters?
Parameter is any attribute Statistic are the measured values of a parameter. A statistic is a sample value such as the average height of a group of students. A parameter is a functional constant such as the mean of a normal distribution. Statistics are often used to estimate parameters. For instance, a sample average is an estimate of the mean.
Is point estimate a range of values used to estimate a population parameter?
mabye, mabye not
What is Hypothesis Testing of Point Estimate?
A statistical estimate of the population parameter.
What is the the relationship between population and sample parameter and statistic?
The relations depend on what measures. The sample mean is an unbiased estimate for the population mean, with maximum likelihood. The sample maximum is a lower bound for the population maximum.
What is the difference a parameter and a statistic?
A parameter is a number describing something about a whole population. eg population mean or mode. A statistic is something that describes a sample (eg sample mean)and is used as an estimator for a population parameter. (because samples should represent populations!)
Does a parameter describe a population or a sample?
A parameter describes a population. A statistic describes a sample.
What is the single parameter in the binomial distribution and what sample statistic would be used to estimate it?
The binomial distribution is defined by two parameters so there is not THE SINGLE parameter.
Does a random largely selected sample always give a better estimate of the population than a randomly selected sample?
A larger random sample will always give a better estimate of a population parameter than a smaller random sample.
A numerical summary of a population is a?
Parameter
What are the main qualities of a good estimator?
A "Good" estimator is the one which provides an estimate with the following qualities:Unbiasedness: An estimate is said to be an unbiased estimate of a given parameter when the expected value of that estimator can be shown to be equal to the parameter being estimated. For example, the mean of a sample is an unbiased estimate of the mean of the population from which the sample was drawn. Unbiasedness is a good quality for an estimate, since, in such a case, using weighted average of several estimates provides a better estimate than each one of those estimates. Therefore, unbiasedness allows us to upgrade our estimates. For example, if your estimates of the population mean µ are say, 10, and 11.2 from two independent samples of sizes 20, and 30 respectively, then a better estimate of the population mean µ based on both samples is [20 (10) + 30 (11.2)] (20 + 30) = 10.75.Consistency: The standard deviation of an estimate is called the standard error of that estimate. The larger the standard error the more error in your estimate. The standard deviation of an estimate is a commonly used index of the error entailed in estimating a population parameter based on the information in a random sample of size n from the entire population.An estimator is said to be "consistent" if increasing the sample size produces an estimate with smaller standard error. Therefore, your estimate is "consistent" with the sample size. That is, spending more money to obtain a larger sample produces a better estimate.Efficiency: An efficient estimate is one which has the smallest standard error among all unbiased estimators.The "best" estimator is the one which is the closest to the population parameter being estimated.
Does the confidence interval always contain the true population parameter?
No, the confidence interval (CI) doesn't always contain the true population parameter. A 95% CI means that there is a 95% probability that the population parameter falls within the specified CI.
How does a parameter and a statistic differ?
A parameter is a numerical measurement of a population; a statistic is a numerical measurement of a sample.
Standard deviation considered a crude measure of variance?
No. Well not exactly. The square of the standard deviation of a sample, when squared (s2) is an unbiased estimate of the variance of the population. I would not call it crude, but just an estimate. An estimate is an approximate value of the parameter of the population you would like to know (estimand) which in this case is the variance.
