Business Decision Making Project Part 3

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Purpose of Assignment

This assignment provides students with practice in understanding when or why ANOVA and linear regression are identified based on parameters. Students will learn to implement these statistical measures for better business decision-making.

Assignment Steps

Resources: Week 5 Videos; Week 5 Readings; Statistics Lab

Tutorial help on Excel® and Word functions can be found on the Microsoft® Office website. There are also additional tutorials via the web offering support for Office products.

Prepare an 11- to 15-slide Microsoft® PowerPoint® presentation for the senior management team based on the business problem or opportunity you described in Weeks 3-4.

Include on the slides what you would want the audience to see (include appropriate visual aids/layout) and include in the speaker's notes section what you would say as you present each slide. If any source material is quoted or paraphrased in the presentation, use APA citations and references.

Draw on material you developed in the Week's 3 and 4 assignments.

Include the following in your presentation:

  • Introduction slide
  • Agenda slide
  • Describe the organization, with a brief description
  • Explain the business problem or opportunity
  • Describe the hypothesis
  • Analyze why the business problem is important
  • Identify what variable would be best to measure for this problem and explain why
  • Identify statistical methods used to analyze data
  • Apply data analysis techniques to this problem (tell which techniques should be used: descriptive statistics, inferential stats, probability) and explain why
  • Apply a possible solution to the problem/opportunity, with rationale
  • Evaluate how data could be used to measure the implementation of such a solution
  • Conclusion
  • Reference slide (if any source material is quoted or paraphrased throughout the presentation)

Format your assignment consistent with APA guidelines.


video

Watch the instructional video by clicking on the Lynda.com® link.

Type the title "Statistics with Excel Part One" in the Search Bar to find the video.

Watch the following tutorials from Section 19:

  • Two-Factor ANOVA

Consider the following as you watch:

  • Discover how to perform a two factor hypothesis test with Microsoft® Excel®

Watch the instructional video by clicking on the Lynda.com® link.

Type the title "Statistics with Excel Part One" in the Search Bar to find the video.

Watch the following tutorials from Section 20:

  • Regression Line Overview

Consider the following as you watch:

  • How can you use Microsoft® Excel® to create a regression line?

Watch the instructional video by clicking on the Lynda.com® link.

Type the title "Descriptive Healthcare Analytics in R" in the Search Bar to find the video.

Watch the following tutorials from Section 6:

  • Introduction to ANOVA and Linear Regression Code

Consider the following as you watch:

  • Demonstrate what Microsoft® Excel® statistical tools are needed to produce a linear regression and ANOVA models.

Unformatted Attachment Preview

BUSINESS DECISION-MAKING PROJECT 1 Business Decision Making Project part 1 Denise Mares QNT/275 July 31, 2017 University of Phoenix BUSINESS DECISION-MAKING PROJECT 2 In a business setting, young people who are educated on decision making should be able to apply statistical concepts in business situations in order to inform data-driven decision making because, in the end, it’s all about the number and their impact. By this, I chose to focus on the Microfinance section where the institutions that major in this field have been paying attention to the increasing information system as it is general knowledge to realize that at the heart of every action done under microfinance, information is the main influencer (Anthony, 1993). In order for the micro financing firm to develop good business practices, they should focus on building the practices that can be sustained through outlining strategies with information technology. The organization should lift up the perception of the information technology to strategic process level and it should be woven and used deeply along with the operations in order to improve on decision –making in a way that it would be a core foundation of competency of the organization. Through this, the micro financing aspect should be managed in accordance to the rubric outlined by the management information software where it would require a massive effort and team contribution in terms of financial efforts and team spirit. ACCION USA is one of the companies that deal with micro financing. ACCION serves various types of businesses all over the country but mostly, the ones based at home. Units that deal with catering, street vendors, and relatively small restaurants are benefiting from ACCION. According to my research and adequate observation, there is a development of a problem in the Micro financing institution that is associated with Management information systems. A management information system is a combination of all the systems where the institution, in this BUSINESS DECISION-MAKING PROJECT 3 case, ACCION, uses for the generation of information that creates a rubric for guiding the management in decision making (Joshi, 2013). There is a great technological development in this age and day, but the diverse and yet complex nature of micro financing creates a difficult encounter for the development of the appropriate software. ACCION needed to come to terms with this situation and through the development of a program that helps with enormous data collection by adopting new technology, such as the management information systems. The dependency of management information systems helps in managing the micro financing institutions by leading the institution towards making the right decisions, developing innovative products and improvement in operations in the firm (Cracknell, David, Henry & Graham, 2004). In micro financing, a large number of transactions take place and this leads to the flow of excess information. The customer-interface and knowledge that ACCIO goes through which are important elements, It needs a system that will handle the information efficiently, therefore, fulfilling the purpose of management information systems (Joshi, 2013). ACCIO has definitely used the benefits of management information systems where there is processing of raw data and transformation of significant information which management can use for decision making. Micro financing institutions such as ACCIO are leaning towards redefining their processes, communication, and integration with the most recent technologies. The management information systems are computer software that derives its conclusions from the process that are taking place on –ground. This means that a Micro financing enterprise such as ACCIO should aim at the integration of timely and accurate information with certification procedures and inbuilt checking programs (Laudon, 2010). BUSINESS DECISION-MAKING PROJECT 4 The current research variable that is derived from the Management information systems based on Micro financing includes the business intelligent techniques and tools, social commerce and mobile payment. Some of the methods that would be the most efficient for this subject for the purpose of data collection through qualitative and quantitative data are through the use of the major steps of research. I believe that they would be effective and significant. First, the identification of the problem and forming a clear and evident hypothesis based on the identification. In this case, micro financing under ACCIO is the management information systems which have a direct and evident effect on the decision-making process of ACCIO. Secondly, designing the research by determining how I would collect the data that will support my argument on management information systems and their impact on micro financing under ACCIO. Under this, there can be the utilization of non-experimental approach which requires an accurate description of the problem but there are no attempts of determining the cause and effect of the connection of re variable against the outcome. For instance field studies, literature reviews. Although in this setting this approach if taken wouldn’t yield the best results. The experimental research approach would be the most appropriate approach as it requires the scientific approach where there are attempts to solve the problem in order to yield results that would be useful. Thirdly by conducting the research in order to support the hypothesis and collection of information under financial management information systems and determining if they would meet ACCIOs financial obligations and goals. After all, this is done, gathering and communication are the last methods that would support the hypothesis and thesis as well as it would be a manifestation that the information acquired and data gathered is, in fact, BUSINESS DECISION-MAKING PROJECT 5 valuable and the problem can be solved through identification of the research variable (Laudon, 2010). All this conduction of research through the experimental basis would lead to a more technological structures management information software that ACCIO can build on the platform as a data base that relates to the entire system and provision of the facility by making inquiries of the database by the user. The performance of the software should be investigated in order to ensure that it supports multiple users who perform activities simultaneously without compromising the performance in terms of accuracy and speed. The micro finance system should focus on building better practices because it determines the future and success of this particular entity (Waterfield, Charles &Nick, 1998). I would know that the data collection method was in fact useful when the software, management information system, is able to complete audit trials for the facilitation of audits, through collection of timely, accurate, reliable, complete and consistent information, when there is provision of adequate management reporting, when there is the facilitation of financial statements preparation and efficient support of the budget preparation and execution. After all this data gathering and analysis, ACCIO should be able to embrace the management information system as it would lead to professional and accurate financial information, less administration required within the business and overall flexibility of additional control over expenditure and reporting matters. BUSINESS DECISION-MAKING PROJECT References Anthony, Robert N. (1993). “Essentials of Accounting – Fifth Edition.” Harvard Business School. Addison-Wesley Publishing Company. Cracknell, David, Henry Sempangi, Graham A.N. Wright.(2004). “Costing and Pricing of Financial Services – A Toolkit.” MicroSave Africa. Joshi, Girdhar (2013). Management Information Systems. New Delhi: Oxford University Press. Laudon, K.,&Laudon, J. (2010). Management information systems: Managing the digital firm. (11th ed.). Upper Saddle River, NJ: Pearson Prentice Hall. Waterfield, Charles, Nick Ramsing. (1998). “Management Information Systems for Microfinance Institutions: A Handbook.” Consultative Group to Assist the Poorest. Technical Tool Series. 6 Business Decision Making Project Pt2 1 Business Decision Making Project Pt2 Denise Mares QNT/275 07/07/2017 University of Phoenix Business Decision Making Project 2 Business Decision Making Project Pt2 There are different types of descriptive statistics that suit different research studies when it comes to the summarizing the data. As far as the study on ACCION USA is concerned, there is a specific type of descriptive statistic that would come in handy to help with the decision making process. Notably, as noted before, the decisions made by ACCION are reached after the organization observes data that has been generated which informs the rubric that guides how the decisions are made in the organization. The measure of central tendency would be the most applicable and strategic type of descriptive statistic which would come in handy in this particular study. The measures of central tendency as a type of descriptive statistics would come in handy in this study which seeks to determine trends in the market through the collection of samples. The mean, median and mode are the three types of measures of central tendency (Weisburd & Britt, 2014). Certain cons are associated with these types of descriptive statistics which would come in handy in the study. Firstly, the model is quite easy to obtain, and also it can be used where there is nominal data. Notably, the business data has a great tendency to be inclined towards nominal data (Weisburd & Britt, 2014). As such, this would be a strategic option. The other two types of measures of central tendency are mean and median. The mean would also come in handy in this study since the method is quite strategic in situations where there is need to determine the measure of central tendency (Park, 2015). This comes in handy since it offers a great reflection on the total score. In the business setup, information on the reflection of a total score is critical since it could be used in the taking of key business steps. For example, when seeking to determine the spending habits of clients, with a mean of how they Business Decision Making Project 3 spend regarding their product preference, a business can be able to change its production strategy to align it to the trends. On the other hand, the median would also come in handy when collecting data since it concentrates on the central point of distribution (Leys et al., 2013). Inferential statistics are inclined towards the use of random sampling. When carrying out inferential statistical observations and data collection, the analysis is done on the properties of data or an item. In this context, the data is analyzed through the testing of hypotheses as well as the driving of estimates as a conclusion. Hypotheses can be used in business research studies to collect data and determine trends based on known or assumed status quo. In such a context, if the researcher were to obtain a sample, the driving of estimates would suffice as a sufficient method of analysis. Notably, in this particular method, a sample is picked, and the analysis is generalized to the larger sample (Simonsohn, Simmons & Nelson, 2015). In business setups, trend analysis is a critical statistical tool that cannot be ignored by the key decision makers. In trend analysis, key business data is analyzed and compared over time to identify the trends therein (Kim et al., 2017). With the findings acquired from trend analysis, businesses can be able to make strategic decisions and to try and achieve the business’ goals. With the business problem that I sought to solve that has to do with how the management information systems impacts on the micro finances of ACCIO, trend analysis will help indicate the trends on the impact. If done well, trend analysis will help me determine the probable direction where the business is heading to regarding the impact of the management information system. Trend analysis could come in handy to help deal with the issue of the management information system in different ways. For instance, when the trends are determined, it will be easy to determine how Business Decision Making Project 4 the system is impacting on the business. To be specific, the analysis will shed light on the areas where the system has been affecting the decision making in both positive as well as negative ways. The study will also help with the determination of the solution to the issue. Linear regression is used in business due to its strategic characteristics of being a true and also pure trend line. In the context of the concept that a trend line remains true, then in linear regression, the trends in business can be mapped out and a technical analysis determined by the trends which is thought to continue on the same line (Montgomery, Peck & Vining, 2015). In a much as the trend can only be said to remain as according to the linear regression findings, the future trend can only be pegged on the analysis for a short time into the future. Nonetheless, the trend sheds light on possible future trends. In this context, the issues faced by the business as far as the influence of the management information system is concerned would most likely remain as they were if the system was to be used in the same way that it was being used in the past. As such, to get different results, the findings from the linear regression analysis would come in handy to determine the changes that need to be made to change the trend. As far as the time series is concerned, this particular method of statistical analysis is based on data that depends on time. This time series analysis enables the researcher to look into the past and determine the status quo of the business at that time (Box et al., 2015). From the findings based on a time series mode of analysis, it is possible and very important to determine how the management information system has been impacting on the decision making at the ACCIO. This analysis also helps the researcher to determine the probable future trend of what has been taking place in the past. Of course this conclusion would be based on the assumption that all factors remain constant. With findings from a researched informed by a time analysis, Business Decision Making Project well-educated decisions will be made on how the management information system ought to be used or whether it needs to be changed to change the results. Conclusively, statistical analysis would help solve the issue with the management information system if done correctly. 5 Business Decision Making Project 6 References Box, G. E., Jenkins, G. M., Reinsel, G. C., & Ljung, G. M. (2015). Time series analysis: forecasting and control. John Wiley & Sons. Kim, H. J., Luo, J., Chen, H. S., Green, D., Buckman, D., Byrne, J., & Feuer, E. J. (2017). Improved confidence interval for average annual percent change in trend analysis. Statistics in Medicine. Leys, C., Ley, C., Klein, O., Bernard, P., & Licata, L. (2013). Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median. Journal of Experimental Social Psychology, 49(4), 764-766. Montgomery, D. C., Peck, E. A., & Vining, G. G. (2015). Introduction to linear regression analysis. John Wiley & Sons. Park, H. M. (2015). Univariate analysis and normality test using SAS, Stata, and SPSS. Simonsohn, U., Simmons, J. P., & Nelson, L. D. (2015). Specification curve: Descriptive and inferential statistics on all reasonable specifications. Weisburd, D., & Britt, C. (2014). Describing the Typical Case: Measures of Central Tendency. In Statistics in Criminal Justice (pp. 65-93). Springer US. Business Decision Making Project Part 3 Grading Guide QNT/275 Version 6 Statistics for Decision-Making Copyright Copyright © 2017, 2016 by University of Phoenix. All rights reserved. University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries. Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation. Edited in accordance with University of Phoenix® editorial standards and practices. Business Decision Making Project Part 3 Grading Guide QNT/275 Version 6 Individual Assignment: Business Decision Making Project Part 3 Purpose of Assignment The purpose of this assignment is to have students demonstrate mastery of their ability to communicate statistical concepts to business leaders to inform business decision-making based on data. This assignment is part 3 of the project began in Week 3 and continued in Week 4. This assignment brings together information students completed in Weeks 3 and 4 and students will format the information suitable for an audience of senior management. Resources Required Week 5 videos; Week 5 readings; Statistics lab; Week 3 Business Decision Making Project Part 1; Week 4 Business Decision Making Project Part 2 Tutorial help on Excel® and Word functions can be found on the Microsoft® Office website. There are also additional tutorials via the web offering support for Office products. Grading Guide Content Introduction slide. Agenda slide. Described the organization, with a brief description. Explained the business problem or opportunity. Described the hypothesis. Analyzed why the business problem is important. Identified what variable would be best to measure for this problem and explained why. Met Partially Met Not Met Comments: 2 Business Decision Making Project Part 3 Grading Guide QNT/275 Version 6 Content Met Partially Met Not Met Total Available Total Earned 5 #/5 Partially Met Not Met Comments: Identified statistical methods used to analyze data. Applied data analysis techniques to this problem (tell which techniques should be used: descriptive statistics, inferential stats, probability) and explained why. Applied a possible solution to the problem/opportunity, with rationale. Evaluated how data could be used to measure the implementation of such a solution. Conclusion slide. Reference slide (if any source material is quoted or paraphrased throughout the presentation). Presentation is 11 to 15 slides. Writing Guidelines Organization The tone is appropriate to the content and assignment. The introduction provides a sufficient background on the topic and previews major points. Paragraph transitions are present, logical, and maintain the flow throughout the paper. The conclusion is logical, flows from the body of the paper, and reviews the major points. Mechanics Met Comments: 3 Business Decision Making Project Part 3 Grading Guide QNT/275 Version 6 The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements. Intellectual property is recognized with in-text citations and a reference page. Sentences are complete, clear, and concise. Rules of grammar and usage are followed including spelling and punctuation. Assignment Total Additional comments: # Total Available Total Earned 1 #1 6 #6 4
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