Week 4 Communicating and Acting on Results Discussion
Khaldoun Post Hello Professors and Classmates! Did your analysis of the data confirm or refute your hypothesis? Explain. I stated that Qualitative forecasting is based on consumer’s and experts’ opinions and judgment in terms of my analysis. This business forecasting method is useful if you have insufficient historical data to make any statistically relevant conclusions. (1) After developing the basis and estimating future business operations, I was confident that this data would lead to a recommendation in favor of the Electronic Health Record Data, my suggestion for change implementation. My data analysis confirmed my hypothesis as, since 2017, nearly 9 in 10 (86%) of office-based physicians had adopted any EHR, and almost 4 in 5 (80%) had adopted a certified EHR. (2) Which data analysis tools among the ones we studied were most useful in analyzing the data you gathered? Explain. Data analysis entails finding consistent patterns; in other words, the relationship among the variables that are embedded in the data (2). The data analysis tools that were the most useful for our data and helped transformed it into information were reporting software such as SAP Business solutions, Microsoft SharePoint, TIBCO Spotfire, and MicroStrategy, along with IBM SPSS. This software has provided the capabilities for graphical display and interactive visual analysis. How will you organize and share your data so that the story it tells is clear and compelling? (See p.17 of Davenport & Kim for a list of types of visual graphics used to present data) The most successful analysts are those who can tell a story with data. (4) Good stories present findings in terms that the audience can understand. We can use a heat map; these are individual values contained in a matrix represented as colors. These will be compared using a bar chart or a bubble chart. Analyzing the test frequencies can be conducted using Tag Cloud or Phrase net. (4) Regards, Khaldoun References: Landau, Business Forecasting: Why You Need It and How to Do It https://dashboard.healthit.gov/quickstats/quickstats.php#:~:text=As%20of%202017%2C%20nearly%209 ,View%20Quick%20Stat, Health IT Quick Stats Davenport & Kim, Ch. 3: Solving the Problem Davenport & Kim, Ch. 4: Communicating and Acting on Results Dunsta’s Post Did your analysis of the data confirm or refute your hypothesis? Explain My research is to analyse how investments into Research and Development will help improve revenue of pharmaceutical companies in the long run. I chose Moderna INC as my main source of data and I used annual financial reports to gather data. My hypothesis was that investments into R&D is needed to increase revenue of pharmaceutical companies. The data I gathered from annual reports suggest that moderna INC continuously increased investments to R7D and it helped them improve revenue. The development of Covid Vaccine is another evidence that show pharmaceutical companies should continue to invest on R&D. Hence the hypothesis was True. Which data analysis tools among the ones we studied were most useful in analyzing the data you gathered? Explain. I used google drive to store my data. Data analysis was performed using SPSS 24 software. The graphs and comparisons were made using this software. How will you organize and share your data so that the story it tells is clear and compelling? I will first highlight the importance of my topic considering the gloabal pandemic we are facing. The narrative will begin from pre covid to the present and how development of a vaccine was front page news for over a year now. Hence companies who invested in R&D were the front runners to develop a safe vaccine. I will be using graphs, histograms and tables to show data in an orderly manner. All explanations will be backed by evidence. Dunstan References Davenport & Kim, Ch. 4: Communicating and Acting on Results JWI 581, experts of practice videos. Week 4. Cosgrove, T– Technology. …
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