Sampling-Confidence Intervals Answer the following questions over the content ma
ID: 2923372 • Letter: S
Question
Sampling-Confidence Intervals Answer the following questions over the content material you just read or watched. 1. What is sampling variability and why is it important to understand? What is a sampling distribution and what characteristics will it have if formed from a simple random sample? 2. 3. what is the formula for an 80% confidence interval for a population proportion? 4. what is the correct interpretation of a 95% confidence interval? 5. Specify an interval to the right of the parameter p where you can expect about 5% of all the sample proportions to fall.Explanation / Answer
We are allowed to do 1 question at a time. Post again for second question.
1) Random samples from these large populations are used to estimate information about the population parameters. The term "sampling variability" refers to the fact that the statistical information from a sample (called a statistic) will vary as the random sampling is repeated.
Sampling variability is how much an estimate varies between samples. “Variability” is another name for range; Variability between samples indicates the range of values differs between samples.
Sampling variability is often written in terms of a statistic. The variance (2) and standard deviation () are common measures of variability. You might also see reference to the variability of the sample mean (x&772;), which is just another way of saying the sample mean differs from sample to sample. Sampling variability only refers to a statistic (i.e. a number generated from a sample) — never a population.
It is important to understand because it tells about the spread of the data. If there are outliers or not, usual or unusual values are there or not.
It tells us how accurately the sample represents the entire population.
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.