Answer:
Correct option:
"The distribution of the statistic in all possible samples of size <em>n</em> from a given population."
Step-by-step explanation:
The sampling distribution is a probability distribution of a sample statistic.
A sample statistic is a numerical value representing a characteristic of a sample. For example, the sample mean represents the mean value of the sample, the sample variance represent the variance of the sample. Both of these values are sample statistic.
A statistic is an unbiased estimator of the parameter value.
That is, the sample mean value can be used to estimate the value of population mean.
If various large samples are taken from a population and the sample statistic value is computed for each of these samples, then the probability distribution of theses sample statistic is known as the sampling distribution.
The mean of the sampling distribution is same as the population mean and the standard deviation of the sampling distribution is known as the standard error.
The correct option is:
"The distribution of the statistic in all possible samples of size <em>n</em> from a given population."
Answer:
Step-by-step explanation:
Let 'x' be the usage in kWh. When usage is at or under 800 kWh, the cost function C(x) is given by the base charge of $8 added to the rate of $0.05/kWh multiplied by the consumption 'x', in kWh.
Therefore, for 0 ≤ x ≤ 800, the cost function is:
12 is <em>50% </em>less than 24 since 12 is half of 24.
