Answer:
a, also there is a calculator on google for this, if you have any more!
Step-by-step explanation:
Answer:
Sorry, I can't type well.
<span>Given that A
dataset shows that, on average, smokers do not live as long as
nonsmokers and heavy smokers do not live as long as light smokers.
If
you compute the least squares line for y = age at time of death and x =
number of packets per day typically smoked, you will notice that as the number of packets per day a person smokes increases, the age at time of death of the person decreases.
Thus, the graph wil have a negative slope.
Therefore, the slope of your
regression line will be less than 0.</span>
Answer:
The mean birth weight for the sampling distribution is
3,500 grams.
Step-by-step explanation:
The sample mean is the average of the sample values collected divided by the number of the samples, while the population mean is the average or mean of all the values in the population. If the sample is random and the sample size is large enough, then the sample mean would be a good estimator of the population mean. This implies that with a randomly distributed and unbiased sample size, the sample mean and population mean will be equal, according to the central limit theorem. Therefore, the mean of the sample means will always approximate the population mean.