Hopes this helps
I used this app called Cymath.
Answer:
Answer:
Step-by-step explanation:
on the triangle.
I think that is right as I just was reading on this.
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.
Answer:
ML = √[¼ (EC)²]
Step-by-step explanation:
ML² = ½(QR)²
QR² = ½(EC)²
so, ML² = ¼ (EC)²
=> ML = √[¼ (EC)²]
