Question

Problem 3 Weight reduction is an important goal for the management of type 2 diabetes (T2D) among overweight patients. A 2016 study evaluated the effect of oat intake (a cereal grain) for overweight T2D patients. A total of 298 overweight T2D subjects (BMI of at least 24 kg/m2) were randomly assigned to follow one of 4 dietary guidelines for 30 days, as shown in the diagram below. The two “oats” groups ate the same healthy diet as the “diet" group, but some of their daily food intake had to be a given amount of oats. Weight loss at the end of these 30 days was assessed (in kg) for each participant Participants with BMI224 kg/m2 (n=298) Usual care group (n=60) Diet group (n=79) 50g-oats group (n=80) 100g-oats group (n=79)

Answer 1

Which inference procedure should be used? one sample or matched-pairs t procedure for a mean ANOVA for several means two sample t procedure for two means z procedure for a proportion chi-square for two-way tables Question 18 1 pts What are the conditions for this inference procedure? One random sample AND normal data or large enough sample size. One random sample AND large enough counts of successes and failures in the sample. Independent random samples AND normal data or large enough total sample size AND similar sample standard deviations. Independent random samples AND normal data AND large enough total sample size. Random selection without repeated measures AND large enough expected counts. One random sample AND normal data AND large enough sample size. Independent random samples AND normal data or large enough total sample size. Normal data AND large enough expected counts. Independent random samples AND normal data AND large enough total sample size AND similar sample standard deviations.

Would we be able to reach a causal conclusion from such a study? O Yes, because the study is a randomized experiment. O No, because of all the confounding variables. O No, because the study has an observational design. Yes, because we have a large enough combined sample size to utilize the central limit theorem. O No, because we do not have large enough expected counts.