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# Chocolate and BMI

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I need some help with this case study review and identify everything that is required. Thanks
The readings for this week focus on various types of correlations and regressions. In this discussion we will apply those concepts to the analysis of a case study. Read the "Chocolate and Body Weight" case study presented in Chapter 20 of the Online Statistics Education text, as well as the original article by Golomb et al. (2012) linked in the chapter.
In the body of your posting, include an overview of the following based on the research questions, "What is the relationship between chocolate consumption and body mass index (BMI)?"
• Hypotheses: List the statistical notation and written explanations for the null and alternative hypotheses for the study.
• Variables: Describe the independent (predictor) and dependent (outcome) variables, their levels, operational definitions, and characteristics (e.g., scale of measurement).
• Data Analysis: Use the results and Table 1 in the article to analyze the results. Summarize the specific type of statistical test conducted, the results obtained, and conclusions regarding the hypotheses (e.g, can we reject at the .05 or .01 level?). Be sure to describe why this specific correlation/regression was selected.
• Critique: Critique the results of the study, paying specific attention to the appropriateness of the analyses conducted, any biases or assumptions that were made, practical significance of the results, and recommendations for improving upon the study (methods or analyses).

https://brainmass.com/statistics/multivariate-statistics/chocolate-bmi-616101

#### Solution Preview

Chocolate and Lower Body Weight

Research conducted by: Beatrice A. Golomb, Sabrina Koperski, and Halbert L. White

Case study prepared by: Robert F. Houser and Georgette Baghdady

Overview
Recent research has brought to light the beneficial health effects of chocolate. Studies have linked chocolate with lower blood pressure, lower bad cholesterol, improved insulin sensitivity, and reductions in the risks of diabetes, heart disease, and stroke. The authors of this study hypothesized that chocolate's healthful metabolic mechanisms might also reduce fat deposition in spite of its high caloric content.
This study used the baseline data from a clinical study that examined noncardiac effects of cholesterol-lowering drugs in healthy adults. The baseline data included body mass index (BMI), chocolate consumption frequency, age, sex, physical activity frequency, depression, and some dietary variables. Chocolate consumption frequency was assessed with the question: "How many times a week do you consume chocolate?" Dietary intakes of total calories, fruits and vegetables, and saturated fat were assessed with a validated food frequency questionnaire. A food frequency questionnaire is a limited checklist of foods and beverages with a frequency response section for subjects to report how often each item was consumed over a specified period of time. Depression was measured with a validated scale related to mood. BMI is a measure of body fatness that is associated with many adverse health conditions.

What can we conclude from the researchers' findings that there is an association between consuming chocolate frequently and lower BMI? How do we interpret regression models?
Design Issues
The authors used baseline data from an unrelated clinical study examining noncardiac effects of cholesterol-lowering drugs. That clinical study included men ranging in age from 20 to 85 years, but only postmenopausal women. The results of the chocolate study cannot, therefore, be generalized to younger adult women. Except for BMI, the data for all of the study variables were "self-reported" by the subjects via questionnaires. The assessment of critical variables, such as chocolate consumption frequency and vigorous physical activity frequency, could differ when using different measurement tools. The study was cross-sectional in nature, precluding conclusions about causation.

Descriptions of Variables
VARIABLE DESCRIPTION
BMI Body mass index, calculated as:
(weight in kilograms) / (height in meters)2
Chocolate consumption frequency Number of times per week a subject consumed chocolate ...

#### Solution Summary

The readings for this week focus on various types of correlations and regressions. In this discussion we will apply those concepts to the analysis of a case study.

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