SELECT (D) No, the sample size is not large enough. With a range that large, your small survey isn't saying much. Knowing $\sigma$ (you usually don't) will allow you to determine the sample size needed to approximate $\mu$ within $\pm \epsilon $ with a confidence level of $1-\alpha$. And the rule of thumb here is that you would expect per sample more than 10 successes, successes, successes, and failures each, each. B) A Normal model should not be used because the sample size, 12 , is larger than 10% of the population of all coins. If your population is less than 100 then you really need to survey all of them. a. Many researchers use one hard and one soft heuristic. Its the +/- value you see in media polls. I am guessing you are planning to perform an anova. Determining sample size is a very important issue because samples that are too large may waste time, resources and money, while samples that are too small may lead to inaccurate results. In the case of the sampling distribution of the sample mean, 30 30 is a magic number for the number of samples we use to make a sampling In many cases, we can easily determine the minimum sample size needed to estimate a process parameter, such as the population mean. Remember that the condition that the sample be large is not that nbe at least 30 but that the interval. Sample sizes may be evaluated by the quality of the resulting estimates. Here's the logic: The power of every significance test is based on four things: the alpha level, the size of the effect, the amount of variation in the data, and the sample size. The minimum sample size is 100. One that guarantees that the event occurs b. an artifact of the large sample size, and carefully quantify the magnitude and sensitivity of the effect. Normal condition, large counts In general, we always need to be sure were taking enough samples, and/or that our sample sizes are large enough. To calculate your necessary sample size, you'll need to determine several set values and plug them into an In some situations, the increase in precision for larger sample sizes is minimal, or even non-existent. The most common cause of dehydration in young children is severe diarrhea and vomiting. False A sufficient condition for the occurrence of an event is: a. Lets start by considering an example where we simply want to estimate a characteristic of our population, and see the effect that our sample size has on how precise our estimate is.The size of our sample dictates the amount of information we have and therefore, in part, determines our precision or level of confidence that we have in our sample estimates. In a population, values of a variable can follow different probability distributions. Sample sizes equal to or greater than 30 are considered sufficient for the CLT to hold. True b. A) A Normal model should not be used because the sample size is not large enough to satisfy the success/failure condition. Anyhow, you may rearrange the above relation as follows: In some cases, usually when sample size is very large, Normal Distribution can be used to calculate an approximate probability of an event. The larger the sample size is the smaller the effect size that can be detected. How do we determine sample size? QUESTION 2: SELECT (A) Conditions are met; it is safe to proceed with the t-test. A key aspect of CLT is that the average of the sample means In other words, conclusions based on significance and sign alone, claiming that the null hypothesis is rejected, are meaningless unless interpreted Determining whether you have a large enough sample size depends not only on the number within each group, but also on their expected means, standard deviations, and the power you choose. 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