the x values as in the point (3,4) the domain would be 3
1
If you're estimating a point OUTSIDE the data range, it's extrapolating. If you're estimating a point WITHIN the data range, it's interpolating.
True.
If the points have both positive y-values and x-values it is quadrant 1 If the points have a negative x-value and a positive y-value it is quadrant 2 If the points have both negative y-values and x-values it is quadrant 3 If the points have a positive x-values and a negative y-value it is quadrant 4
point estimate
A statistical estimate of the population parameter.
A point estimate is a single value (statistic) used to estimate a population value (parameter)true apex
A point estimate of a population parameter is a single value of a statistic. For example, the sample mean x is a point estimate of the population mean μ. Similarly, the sample proportion p is a point estimate of the population proportion P.
A point estimate is a single value used to estimate a population parameter, such as the sample mean used to estimate the population mean. Confidence intervals can also be used to provide a range within which the population parameter is likely to lie.
Well, isn't that just a happy little mistake! When you survey the entire population, you're looking at the actual parameter, not an estimate. A point estimate comes from sampling just a portion of the population, giving you an idea of what the parameter might be. Just remember, there are no mistakes in statistics, only happy little accidents!
B. The sampling error
To compute the point estimate of a population mean, you take the sample mean. This is done by calculating the average of the data values in the sample. The sample mean is then used as an estimate of the population mean.
Many of the quantitative techniques fall into two broad categories: # Interval estimation # Hypothesis tests Interval Estimates It is common in statistics to estimate a parameter from a sample of data. The value of the parameter using all of the possible data, not just the sample data, is called the population parameter or true value of the parameter. An estimate of the true parameter value is made using the sample data. This is called a point estimate or a sample estimate. For example, the most commonly used measure of location is the mean. The population, or true, mean is the sum of all the members of the given population divided by the number of members in the population. As it is typically impractical to measure every member of the population, a random sample is drawn from the population. The sample mean is calculated by summing the values in the sample and dividing by the number of values in the sample. This sample mean is then used as the point estimate of the population mean. Interval estimates expand on point estimates by incorporating the uncertainty of the point estimate. In the example for the mean above, different samples from the same population will generate different values for the sample mean. An interval estimate quantifies this uncertainty in the sample estimate by computing lower and upper values of an interval which will, with a given level of confidence (i.e., probability), contain the population parameter. Hypothesis Tests Hypothesis tests also address the uncertainty of the sample estimate. However, instead of providing an interval, a hypothesis test attempts to refute a specific claim about a population parameter based on the sample data. For example, the hypothesis might be one of the following: * the population mean is equal to 10 * the population standard deviation is equal to 5 * the means from two populations are equal * the standard deviations from 5 populations are equal To reject a hypothesis is to conclude that it is false. However, to accept a hypothesis does not mean that it is true, only that we do not have evidence to believe otherwise. Thus hypothesis tests are usually stated in terms of both a condition that is doubted (null hypothesis) and a condition that is believed (alternative hypothesis). Website--http://www.itl.nist.gov/div898/handbook/eda/section3/eda35.htmP.s "Just giving info on what you don't know" - ;) Sillypinkjade----
No. The average of a dataset is the point estimate for the mean of the population.
Nearly true. It is a point estimate, not point ofestimate.
he population mean