Stic When testing a new treatment, what is the difference between statistical significance and practical significance? Can a treatment have statistical significance, but not practical significance? ...... Choose the correct answer below. O A. Statistical significance is related to whether common sense suggests that the treatment makes enough of a difference to justify its use. Practical significance is achieved when the result is very unlikely to occur by chance. It is possible for a treatment to have statistical significance, but not practical significance. O B. Statistical significance is achieved when the result is very unlikely to occur by chance. Practical significance is related to whether common sense suggests that the treatment makes enough of a difference to justify its use. It is not possible for a treatment to have statistical significance, but not practical significance. O C. Statistical significance is achieved when the result is very unlikely to occur by chance. Practical significance is related to whether common sense suggests that the treatment makes enough of a difference to justify its use. It is possible for a treatment to have statistical significance, but not practical significance. O D. Statistical significance is related to whether common sense suggests that the treatment makes enough of a difference to justify its use. Practical significance is achieved when the result is very unlikely to occur by chance. It is not possible for a treatment to have statistical significance, but not practical significance.

If a significance test gives p-value 0.005... A.. the effect of interest is practically significant B...We do have good evidence against the null hypothesis C...we do not have good evidence against the null hypothesis D...the null hypothesis is very likely to be true E.. The margin of error is 0.005

Discuss the basic epidemiology measures used in the Colorado uranium miners study. Specifically what measure of risk was used? How was risk calculated? (Hint: Consider a 2 by 2 table to display the data). Do you agree with the authors' conclusions? What would you infer from the data? Why?

“Bullying,” according to noted expert Dan Olweus, “poisons the educational environment and affects the learning of every child.” Suppose you are interested in the emotional well-being not only of the victims but also of bystanders, bullies, and those who bully but who are also victims (bully-victims). You decide to measure anxiety in a group of bullies and a group of bully-victims using an 18-item, 5-point anxiety scale. The group of 84 bullies scored an average of 40.1 with a sample standard deviation of 3.8 on the anxiety scale. The group of 67 bully-victims scored an average of 46.8 with a sample standard deviation of 11.6 on the same scale. Suppose you intend to conduct a hypothesis test on the difference in population means. In preparation, you identify the sample of bullies as sample 1 and the sample of bully-victims as sample 2. Organize the provided data by completing the following table:

In Bayesian statistics, a 90% credible interval (or Bayes interval) covers the true parameter with (subjective) probability 90%. True False

Determine whether the results below appear to have statistical significance, and also determine whether the results have practical significance. In a study of a weight loss program, 6 subjects lost an average of 49 lbs. It is found that there is about a 23% chance of getting such results with a diet that has no effect. (... Does the weight loss program have statistical significance? OA. Yes, the program is statistically significant because the results are unlikely to occur by chance. OB. Yes, the program is statistically significant because the results are likely to occur by chance. OC. No, the program is not statistically significant because the results are likely to occur by chance. O D. No, the program is not statistically significant because the results are unlikely to occur by chance. Does the weight loss program have practical significance? O A. No, the program is not practically significant because the amount of weight lost is trivial. O B. Yes, the program is practically…

What is the base rate(or prevalence in medical literature) and sensitivity(the percentage of individuals with a disease who are correctly classified as having the disease?)

It's important to understand that hypothesis testing is just how statisticians (by "statisticians" I mean people who are working with data, e.g. analysts, auditors, economists, whoever) answer quanitative questions. We intuitively know that not much is truly certain, and that it's really hard (if not impossible) to collect data on everything we are curious about. So we use samples and try to extrapolate to a larger population. For this discussion, I would like each of you to come up with your own interesting hypothesis test. So, you will do the following: 1) Explain the context or story for which you have a problem stats might be able to help with. 2) Come up with the null and alternative hypotheses. This can be in words, or numbers, or a combination of both (I'll give an example below). 3) Explain where/how you might collect data to reach a conclusion for the test. 4)  (RESPONSE) When you respond to someone else's post, I want you to critique their test and data. If you can, suggest a…

Or the given scenario determine the type of error that was made if any.( Hint:Begin by determining the null and alternative hypothesis.) Economists considered a $3.110 as the mean price for a gallon of unleaded gasoline in the United States in a certain year. One consumer claims that the main price for a gallon of unleaded gasoline in the United States in a certain year is different from $3.110. The consumer conducts a hypothesis test and fails to reject the null hypothesis. Assume that in reality the main price for a gallon of unleaded gasoline in the United States in a certain year is $3.21. Was there an error made?if so what type?