Ans. Sampling error - it is any type of bias that is attributable to mistakes in either drawing a sample or determining the sample size
Sampling error is the difference between data obtained from random sampling and data obtained from entire population
A sample is a subset of a population who is selected to participate in a research study and that represent the whole population
Sampling two types
1. Probability sampling
- simple random sampling
- stratified random sampling
- cluster random sampling
- systematic random sampling.
2. Non probability sampling
- convenience
- quota sampling
- purposive sampling
Explain how sampling error can affect a researcher's ability to generalize the results of a study...
After viewing the powerpoint on for chapter 12 answer the following: 1. How do inclusion and exclusion criteria contribute to increasing the strength of evidence by the sampling strategy of a research study? 2. Why is it important for a researcher to use power analysis to calculate sample size? How does adequate sample size affect subject mortality, representativeness of the sample, the researcher's ability to detect a treatment effect, and your ability to generalize the study findings to your patient...
A) A researcher believes that a particular study exhibits large sampling error. What does the researcher mean by sampling error? B) How can sampling error be diminished? C) Discuss why one of the following methods of sample selection might yield sampling error: convenience, snowball, or judgmental.
What is hypothesis testing? How would you explain it to someone who has not had as much statistical experience as you? What is the difference between the null and alternate hypotheses? What does the p-value tell you? When do you reject the null hypothesis or fail to reject the null hypothesis? Explain how collecting data (i.e. convenience sampling, randomly selected sample, etc.) for the samples could impact the ability to generalize your results to the whole population.
Explain the difference between ‘sampling bias and ‘sampling error’, and a how a researcher would decrease sampling error and sampling bias. Explain why reducing each is important for testing a hypothesis.
explain calculatior functions as well please. Find the indicated probability or percentage for the sampling error. 8) Scores on an aptitude test are distributed with a mean of 220 and a standard deviation of 30. The shape of the distribution is unspecified. What is the probability that the sampling error made in esti mating the population mean by the mean of a random sample of 50 test scores will be at most 5 points? A) 0.762 B) 0.881 C) 0.135...
Understanding the sampling process will contribute to your ability to critique research from a consumer's point of view. This week's Forum Discussion will help you to develop your sampling strategy based upon your PICOT. It should be approached in relation to the parameters or attributes of the study population, representative of the defined population, appropriateness of the sampling plan to the research design, appropriateness and justification of the sample size, and evidence that the rights of human participants (subjects) have...
In your own words, explain what sampling error is. Why is sampling error such an issue when it comes to inferential statistics. What is alpha? What does it represent in hypothesis testing? Now that you know a little more about hypothesis testing, how do you feel about the fact that hypothesis testing will never give you a certain answer—that there’s always a possibility of creating a Type I or Type II error?
If you wish to estimate a population mean with a sampling distribution error SE = 0.34 using a 95% confidence interval and you know from prior sampling that σ² is approximately equal to 5.9, how many observations would have to be included in your sample?
Im asking this again because the last answer was not helpful. researcher's conciusion correct? Explain your answer. 16. In a population, μ 100 and σ,-25. A sample of 150 people has X- 120. Using two tails and the 05 criterion: (a) What is the critical value? (b) Is this sample mean in the region of rejection? How do you know? (c) What does the mean's loca- tion indicate about the likelihood of this sample occurring in this population? (d) What...
If you wish to estimate a population mean with a sampling distribution error SE= 0.33 using a 95% confidence interval and you know from prior sampling that is approximately equal to 7.6, how many observations would have to be included in your sample? The number of observations that would have to be included in your sample is (Round up to the nearest observation.)