# data[].attributes.body
Be sure to read  the paper "Chocolate with high cocoa content as a weight-loss accelerator" that is linked on Canvas.

Part of our job as scientists is to provide voluntary peer reviews of articles that have been submitted to journals to provide feedback on the scientific quality of the article. This week you will collaborate as a team of reviewers of the study on weight loss and chocolate.

Based on what you have learned about data analysis so far in the course can you suggest any ways to strengthen this paper? Is there any important information missing? What is the N? Are there other demographics to note? Was the statistical analysis done appropriately?

You do not need to wait until your team meeting to get started and you should return to the Padlet a couple of times through out the week to see what your teammates have said and to provide new comments.

I haven't provided question prompts this time. You should use text posts rather than videos this time unless you really want to use a video - go ahead. Photos illustrating your points are great too!

This assignment is worth 15 points. I'd like you each to make 3 posts at two different times this week (feel free to revisit more often) for 5pts each.

# data[].attributes.body
This essay can be improved in several aspects:

It should clarify the Study Design, whether it is an experimental study or observational study, each type has different strengths and weaknesses. The intervention methods such as the amount and frequency of high cocoa content chocolate consumption should be included to make a better compare with control group.

It should also include a comprehensive literature review that discusses previous studies on the relationship between chocolate consumption and weight loss. This will provide context and support for the study's hypothesis.

The detailed statistical analysis should also be added, apart from t-tests, we can also use ANOVA or regression based on the data types and distributions. Discussions about checks for assumptions such as normality, homogeneity of variances, and independence of observations are important.

The essay should also include discuss any potential biases (e.g., selection bias, measurement bias) and confounders that could affect the results. The scope of applicability for the results should be pointed out, including limitations due to the sample characteristics.

# data[].attributes.body
Reports about complete results is missing. We should include descriptive Statistics like means, medians, standard deviations, and ranges to give a full picture of the data. Reports about confidence intervals, p-values, and effect sizes will allow readers to understand the uncertainty and magnitude of the findings.

To help better realize data Visualization, we can use more tables and figures to present complex data more accessibly, aiding in the interpretation of results, like bar charts, boxplot and histograms.

# data[].attributes.body
The exact N (sample size) is not clearly mentioned in the question. This is crucial for understanding the statistical power of the study. Other demographic information is not considered in this essay, such as socioeconomic status, lifestyle habits, and dietary restrictions, which could influence the results. Income can influence dietary choices and access to certain types of food, including high cocoa content chocolate, while education might affect understanding of nutrition and health information, which could influence compliance with the study protocol and outcomes. The levels of physical activities, smoking and alcohol consumption and health status can significantly affect weight loss and should be controlled for in the analysis.

# data[].attributes.body
The research paper can be improved by providing more information about the information of the study participants. In the paper, the authors stated that they selected men and women between the ages of 19-67 and that two-thirds of the participants were female, and one-third male to reflect the disproportionate number of female dieters in the general public. However, the researchers did not mention how the ages of the participants of the study were distributed. The elderly’s metabolism might be different from younger populations and might influence the study's results Therefore, in this case, age is a confounding variable, and its influence is not closely examined. Providing a histogram showing the distribution of age can further strengthen the research.

# data[].attributes.body
The researchers used an independent t-test to compare the participants’ weight loss between the groups and used regression techniques to model the daily weight development by group. This gives readers a general view of how high-cocoa-content chocolate accelerates weight loss. The research can be further improved by creating line plots showing weight reductions. The researchers can also conduct a paired t-test by comparing the weight of the participants before and after the three-week experiment period. This can further validate that chocolate can effectively help reduce weight.

# data[].attributes.body
Finally, the research only briefly discussed that the participants of the chocolate group observed a reduction in exhaustion symptoms and used bar charts to demonstrate the results of the Giessen Subjective Complaints List. I think can provide additional information and interpretation about results, such as plotting the data points and providing the standard deviation of the test scores. Moreover, they can try to offer less data in figure 4 because currently, it is hard for readers to align the bars to the corresponding labels.

# data[].attributes.body
The paper does not clarify the N value. It should provide detailed demographic information about the participants such as age, gender and ethnicity. And also mention about other significant factors besides age (19-67). Ensure the control group is well described and explain how participants were assigned to each group(random or not). Also it would be better to tell if there was any blinding involved to reduce errors (such as were the participants know they had choclate or not).

# data[].attributes.body
The paper should intepret the statistical methods used to get the relationship of weight loss between groups. And it should report the significance levels (p-values). For example, how significant was the 10% greater weight loss in the chocolate group? Furthermore, there are many missing information: although the paper mentions flavonoids, it could be better to provide a more detailed explanation of the biological mechanisms of how it works to help losing weight. Also explain how the study follow up with participants to get the conclution of maintainess.

# data[].attributes.body
The paper should clarify how the participants were monitored and provide a statistic data about the activity level of the participants. Without these information, there are a lot concerns about the reliability of the experimental results. To make the conclusion more persuasive, some statistical images such as the distribution of the participants' ages should be added on. All in all, there are no exact datas show up and a lot of things need to be clarified.

# data[].attributes.body
To make the paper stronger, there are a few key things we could do. One big improvement would be to increase the size of the sample we're studying. This not only gives us more confidence in our results but also makes them more relevant to a wider group of people. Another important step would be to really focus on reducing any biases that could sneak into our findings.

Another thing we could do is use randomization when we're assigning people to different groups in our study. This helps ensure that our results aren't skewed by factors we didn't account for. It's all about making sure our findings truly reflect what's going on and aren't just coincidental.

# data[].attributes.body
The paper is missing important information that would make it more reliable. Specifically, it doesn't say how many people were in the study, which makes it hard to know if the results are strong enough. Also, there's no information about the ages, genders, or backgrounds of the participants, so it's unclear if the findings apply to different kinds of people. Lastly, there's no mention of how the researchers tried to make sure their results weren't affected by biases. Fixing these things would help us understand the study better and see how it could apply to more people.

# data[].attributes.body
It's important to describe the specific statistical methods used in the study to test its claims. Whether it was experimental or observational, and providing values for p-values and confidence intervals, would help show how reliable and meaningful the findings are. These details are key to making sure the conclusions are based on solid statistical analysis.