A point estimate is a single value (statistic) used to estimate a population value (parameter)true apex
B. The sampling error
Either.
Parameter
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.
mabye, mabye not
A statistical estimate of the population parameter.
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.
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!)
A parameter describes a population. A statistic describes a sample.
The binomial distribution is defined by two parameters so there is not THE SINGLE parameter.
A larger random sample will always give a better estimate of a population parameter than a smaller random sample.
Parameter
Well, honey, a good estimator needs to have a keen eye for details, a solid understanding of the project scope, excellent math skills, and the ability to make educated guesses without breaking a sweat. Basically, they need to be part Sherlock Holmes, part human calculator, and all-around badass at predicting costs. So, if you're looking for someone to estimate your project like a pro, make sure they've got these qualities in spades.
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.
A parameter is a numerical measurement of a population; a statistic is a numerical measurement of a sample.
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.