I need a 4 pages word format, 15 slides of presentation and an exective summary.This is the last assignment in the course and we should use the information from the previous assignments. I can attach all 7 previous assignments (average of 4 pages per an assignment) to help you get it done, its a basic requirement from the what we've done throughout the course.
Week 1 -M.docx 6 Week 1 - Assignment: Summarize the Lifecycle Components of a Business Case In this article, the business problems had arisen from the recent advances in application of mobile phone and social media data that have many effects in human behaviors which subsequently will shape the growth of Telecom Italia and its profitability! The company focuses were on data-driven studies to answer its main general concern (How the recent advances in the application of mobile phone and social media data could affect individuals and the collective behavior?). The correlational researches conducted to draw a cause-and-effect conclusion followed the scientific method that helped to reach to a conclusion and an answer for the problem. Telecom Italia used case studies as their logical structure to examine one aspect! They provided the type of data needed which included: Acts, behaviors, or events, reports of acts, behavior, or events, demographic data, self-identity, shallow opinions and attitudes, deeply held opinions and attitudes, personal feelings, cultural knowledge, personal and psychological traits data and hidden social patterns data! The data they picked were mainly related to the type of data needed! The data were collected from public and private records, detached observation, participants’ observations, in-depth interviews, Surveys, phenomenological interviews, critical incident interviews, focus groups, and psychological scales and their kin, content analysis, discourse analysis and grounded theory! These wide range of data used were provided by the company and also collected by participants and were matched with the type of data needed! Two locations used as data collection sites (the city Milan and the Trentino province) and from already-existing data collected by company and others! Data used were qualitative and scales of measurement. The study focused to find evidence-based approach that relies on direct observations and experiments in the acquisition of the new knowledge needed! They found out that, the call detail Records (CDRs) and social media can be used in different forms to generate more sustainable, smart and safe cities. The company along with other groups of participants made accurate measurements as they provided a multi-source geo-referenced and anonymized dataset composed from unique sources and from two data collection sites. The company also provided operational definitions for the same phenomenon! Company made available the same dataset to all research teams! (This also was useful for replication later where the company ran a second edition of the challenge.) The research idea translated to many answerable questions as there were hundreds of teams involved and hundreds of researches were completed. Participants (teams) were selected (assigned) carefully and probably which included many members of the population of interest with good considerations for the multiculturalism. Article also specified couple of hypotheses used in some researches on the ‘Telecom Italia Big Data Challenge’ as most projects involved predictions of the relationship between their hypotheses and their research designs to explore the effects on individuals and collective behaviors from social media and CDRs. Author selected four top contributions to share on the article. Each one had different results and recommendations! These selected researchers measured the phenomenon of interest in accurate and reliable manners. Teams used different analysis techniques as they designed different researches, gathered different data and asked different questions as well! The hypotheses examined probably as we received agreeing decisions about rejecting it. They eventually concluded that the phenomenon being studied (CDRs and social media) influenced individuals and collective behaviors (both were strongly related to the phenomenon), however, in this correlational study, we still can’t determine which variable caused the other! Telecom Italia also started conducting a second edition of the challenge with a different group of participants to see whether the same results are obtained! This time will involve more cities and more data to be collected to make sure that the results that were obtained are valid and were not results obtained by chance or error and to establish consistency (reliability). By looking at the selected contributions; the answer of the questions (Conclusions) helped in acquiring new knowledge and achieved the goal from using the scientific research! The goal was to describe the relation between two variables or more. The results were good enough to provide important information regarding the average subscriber and different other groups. Describing the relationship between the variables and increasing the sample size to seven cities (As mentioned on the relationships between sample sizes, margin of error and confidence level) will help in the next round (edition) of the challenge as the previous results from the descriptive researches besides more data collection sites; will help in designing more accurate prediction-based researchers and eventually more understanding of the phenomenon to come up with more accurate identifications of the cause (causes) and answer the research problem. Some units of analysis that used by researches on this case study were, individuals, groups, organizations, geographical units, social interactions and artifacts. Some kind of analysis used were describing, comparing, statistical tests, identifying cause and respondent- centered analysis, researcher-centered analysis, coding and QDA software! The researches selected showed many effective methods used for minimizing or eliminating the impact of many sources of artifacts and bias on the validity of the study findings and different effective methods in controlling participants’ effects! The study also showed a high ethics practices and adherence to protect the study participants as most of (the Nuremberg Code), (the Belmont Report: Summary of Basic Principles), the right to confidentiality, IRB’s procedures and DSMPs were met! Studies results were shared to help further researches and helps advance the progress of science and will improve the overall quality of the research being conducted (only the most well-conducted studies) made it through this process in this article. This will allow other researches in subsequent editions and other researches to replicate the study’s results or extend the study’s finding which will improve the way we live ultimately. These results could also be presented at a professional conference that will provide dissemination of up-to-date research findings. One method they planned and used was to purplish the findings on EPJ Data Science Journal. Which played an important role in determining the overall quality and impact of the study. They followed the typical sections of a manuscript (Title, Abstract, introduction, Methods, Results and discussion). One of the most critical findings (on the case history in scientific method by (B. F. Skinner)) is that human behavior is very hard to predict (measures of behavior are highly variable) and is always changing depending on many factors! He trusts only results obtained from a large number of subjects. The results that were found from the Big Data Challenge were also obtained from a large number of subjects! And this challenge (including the second edition and any other editions) will be a great base for future researches. This type of researches should be ongoing despite the high cost involved, with more sophisticated users, new contents on Social Medias and many other direct factors. The findings should be renewed frequently as the data itself that will be collected every time will be different as well as the analysis methods, and so on. In a fast-based industry like communication; researches should be ongoing to keep getting new knowledge and improve the decision-making process to reach to the ultimate goals. Resources from this week showed that; a case study cannot provide reliable information about the broader class, but it may be useful in the preliminary stages of an investigation since it provides hypotheses, which may be tested systematically with a larger number of cases. The challenge was conducted only on two cities (major cities). For a company that covers the entire country and with this fast-based industry challenges, continuing researching and improving the decision-making process is vital and it could determine and shape its growth in the future. More Big data insights I found on the other resources provided, like the two discussion- based articles (blog posts) and the TED Talks (by Kenneth Cukier). Big data in communication will help companies (like Telecom Italia) to gain new subscribers, retaining customers, and expanding within current subscriber bases, As I’ve noticed that were their business problems and most of the participants had the necessary three skills to deal with Big Data (analyze, process data to drive a business growth). Kenneth addressed brilliant points about big data and its major positive effects on businesses’ success and our lives. I found a couple of points that are directly related to this business case! Data allow us to see things differently if we used it effectively. Collecting more data will increase the accuracy of predictions and that what Telecom Italia did, (They expanded the teams and replicated the studies)! Sharing data will lead to identify more aspects on our lives and will open the door for more knowledge that will lead eventually to more effective results about these aspects, to do so, they should start changing any of these problems to see more effective results (like machine learning effects on social media). Last, I found out also the data have other dark sides besides stealing jobs that is directly related to this article like: (punishing for predictions and safeguarding the freewill or individual choices). Telecom Italia should always adjust big data to the human needs and not miss use it. Big data already transformed how we think, work and live. Telecom Italia should always learn more from big data they collect to improve human lives and make it the ultimate goal (in a top of its own growth and profitability goals). References Lepri, B., Antonelli, F., Pianesi, F., & Pentland, A. (2015). Making Big Data Work: Smart, Sustainable, and Safe Cities. EPJ Data Science, 4(16), 1–4. https://doi.org/10.1140/epjds/s13688-015-0050-4 Castrounis, A. (2017, March 29). What is Data Science, and What Does a Data Scientist Do? KDnuggets. http://www.kdnuggets.com/2017/03/data-science-data-scientist-do.html Cukier, K. (2014, September 23). Big Data is Better Data [Video]. YouTube. http://www.youtube.com/watch?v=8pHzROP1D-w&feature=emb_title Mannappa, A. (2021, January 27). Data Science Vs. Big Data Vs Data Analytics [Updated]. Simplilearn. http://www.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article Marczyk, G., DeMatteo, D., & Festinger, D. (2005). Essentials of behavioral science series: Essentials of research design and methodology. John Wiley & Sons. Ranyard, R., Crozier, W. R., Svenson, O. (1997). Decision Making: Cognitive Models and explanations. ROUTLEDGE. Skinner, B. F. (1956). A case history in scientific method. American Psychologist, 11(5), 221–233. https://doi.org/10.1037/h0047662 Spickard, J. V. (2017). Research Basics: Design to Data Analysis in Six Steps. SAGE Publication. http://lccn.loc.gov/2016026731 Week 2 -M.docx 4 1 Week 2 - Assignment: Draft a Research Plan Based on a General Operational Model (Revised) Health Care & COVID-19 Crises: proactive strategies, more insured 1) Identifying a Research Need The goal of this proposal is to provide highlights about the recent changes in the health ecosystem created by the COVID-19 pandemic and to showcase some of the most challenges that affect temporary unemployed and uninsured individuals over 50 in Denver CO to study the increased barriers for health