Identify a scientific or real-world problem with a relevant data set. Translate the problem into one or two statistical questions involving hypothesis testing and regression. Make sure that the statistical questions are defined narrowly enough for you to tackle within a week. Perform exploratory data analysis and statistical analyses in R. Write a short report (< 1 page of main text), which contains the following parts:

1. Background:
a. Description of the problem;
b. Description of the statistical questions involved;

2. Results: summary of the results from data analysis in layman’s terms, with figures necessary to illustrate the main points.

3. Discussion: discuss why the chosen analysis is done and what limitations there are. Discuss possible future directions: for example, the scientific/real-world problem may be explored in other ways, even though you may not know what statistical analysis to do; or additional data should be collected, etc.

4. Appendix:
a. Details of the statistical analyses; use and define math symbols where necessary.
b. R code used. The R code is expected to have adequate comments for understanding and to be run by another person without debugging.

The report is evaluated in the following aspects:
1. Is the real-world problem clearly stated?
2. Are the statistical questions clearly defined?
3. Are the statistical analyses reasonable? Are the assumptions for these analyses satisfied? If not, what considerations are given and what additional procedures are taken?
4. Do the analysis results make sense in terms of the background and in terms of statistics?
5. Are figures correctly drawn, labeled and referred to in the main text? Are they helpful for understanding the text?
6. Are the results reproducible? In other words, does the R code run without issues and generate the results described in the report?

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These solutions may offer step-by-step problem-solving explanations or good writing examples that include modern styles of formatting and construction of bibliographies out of text citations and references. Students may use these solutions for personal skill-building and practice. Unethical use is strictly forbidden.

The type of media people have the most access to could have the most influence on forming their political views and preference in who they vote for the office. American National Elections Study 2012 complied answers to the survey questionnaire from American voters for the general election of 2012. It includes the self-claimed degree of attention they paid to candidate information. The anecdotal story tells that people who obtain information from printed media, i.e. newspaper form the political view more logically than from TV which makes use of dramatic visual effects and sounds to influence people’s emotion. Another anecdotal story tells that getting information from radio also gives people a processing time of information logically more than TV. It is also interesting to see if those potential effect varies between genders. Several contingency tables are shown in Table 1 on the number of men/female who claim the media they pay a lot of attention to for the candidate information. The casual observation of these tables suggest that more people voted for Barak Obama regardless of which type of media they paid the large attention to expect for the male who paid a lot of attention to the radio. Within each gender, a larger portion of female voted for Obama than male voters....

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