QNT 351 UOP Course,QNT 351 UOP Tutors,QNT 351 UOP Assignments Flashcards
QNT 351 Week 5 Learning Team Analyzing and Interpreting Data (Attachment Contains PowerPoint Presentation and Papers)
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QNT 351 Week 5 Learning Team Analyzing and Interpreting Data (Attachment Contains PowerPoint Presentation and Papers)
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Resource: Ballard Integrated Managed Services, Inc., Part 2.
Read the Ballard Integrated Managed Services, Inc., Part 2. Your team acts as a consultant group that analyzes and interprets this second set of data. The intent is to increase senior management’s understanding of the sources of employee dissatisfaction and to create a model that predicts employee resignation.
Combine your Week Two Learning Team assignment and Week Three findings with Week Five findings and make a recommendation to BIMS.
Use the statistical tables given in the appendices of the textbook and a statistical analysis application: a Microsoft®Excel® spreadsheet, Minitab® statistical software, or SPSS™ software.
Prepare a 1,050- to 1,750-word written report along with a 7- to 9-slide Microsoft® PowerPoint® presentation for the senior management team to present your findings (see Exhibit D for the data set of the second survey).
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QNT 351 Week 5 DQ 3
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QNT 351 Week 5 DQ 3
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What type of data is best described using a Time Series? Think of an example from your work place or from your day to day experience.
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QNT 351 Week 5 DQ 2
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QNT 351 Week 5 DQ 2
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In what way has the learning from this course helped you to effectively test hypotheses, draw conclusions, and provide recommendations to management? Consider what you have achieved in your research study conducted for this course.
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QNT 351 Week 4 Learning Team Reflection
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QNT 351 Week 4 Learning Team Reflection
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Discuss the following with your Learning Team:
· The steps in testing a research hypothesis
· Comparing the means of two or more groups
· Calculating the correlation between two variables
Include the topics you feel comfortable with, any topics you struggled with, and how the weekly topics relate to application in your field.
Prepare a 350- to 1,050-word paper detailing the findings of your discussion.
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QNT 351 Week 4 DQ 4
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QNT 351 Week 4 DQ 4
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Think of an example of the use of one sample hypothesis testing at your workplace. How will you state the hypothesis as a Null and the Alternative hypothesis?
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QNT 351 Week 4 DQ 3
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QNT 351 Week 4 DQ 3
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What are the key terms in a verbal hypothesis that signify whether you are conducting a one–tailed or two-tailed test? Explain with an example and also state the Null and the Alternative hypothesis for the example in symbolic form.
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QNT 351 Week 4 DQ 2
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QNT 351 Week 4 DQ 2
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Under what conditions would you use a t-test as opposed to a z-test? Can you use the t-table to determine the critical value of the z-test? Explain why. What are the differences between a one-tailed and a two-tailed test?
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QNT 351 Week 4 DQ 1
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QNT 351 Week 4 DQ 1
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What are the five steps in the hypothesis testing procedure? Are the steps followed in sequence? Explain why or why not. How does the five-step procedure for hypothesis testing differ when comparing two groups using a t- or z-test? How is the process similar?
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QNT 351 Week 3 Learning Team Summarizing and Presenting Data
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QNT 351 Week 3 Learning Team Summarizing and Presenting Data
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Prepare a 1,050- to 1,750-word report of conclusions drawn from the data and make recommendations to the management.
Support recommendations by citing literature consistent with APA guidelines.
If using the Ballard Integrated Managed Services, Inc., (BIMS) case study overview:
Revise the report submitted in Week Two based on the feedback provided by the instructor in the Learning Team assignment, and insight gained by reading.
Analyze the data included in BIMS case study Part 1 by computing descriptive statistics in the form of tables, charts, measures of central tendency, and variability.
Prepare a 1,050- to 1,750-word report of conclusions drawn from the data and make recommendations to the management.
Support recommendations by citing literature consistent with APA guidelines.
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QNT 351 Week 3 DQ 5
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QNT 351 Week 3 DQ 5
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What are the characteristics of standard normal distribution? The HR department of an organization collects data on employees’ age, salary, level of education, gender, and ethnicity. Which data do you think is more likely to follow normal distribution? Explain why.
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QNT 351 Week 3 DQ 4
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QNT 351 Week 3 DQ 4
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Provide an example of a discrete data in your work situation that at least approximately obeys the four characteristics of the Binomial distribution.
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QNT 351 Week 3 DQ 3
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QNT 351 Week 3 DQ 3
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What is the role of probability concepts in business decision-making? Explain using a specific example.
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QNT 351 Week 3 DQ 2
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QNT 351 Week 3 DQ 2
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What are some conditions under which business decisions are made using subjective probability concepts? Provide at least two examples of subjective probability.
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QNT 351 Week 3 DQ 1
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QNT 351 Week 3 DQ 1
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What are the differences between probability and coincidence? Can the probability be more than 1 or less than 0? Explain why or why not.
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QNT 351 Week 2 Learning Team Data Collection (Attachments Includes Power Point Presentation And Paper)
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QNT 351 Week 2 Learning Team Data Collection (Attachments Includes Power Point Presentation And Paper)
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Resources: Ballard Integrated Managed Services, Inc., Part 1
Review the Ballard Integrated Managed Services, Inc. (BIMS), Part 1 case study overview.
Prepare a 700- to 1,050-word written report along with a 5- to 7-slide Microsoft® PowerPoint® presentation for the senior management team to present your findings (see Exhibit D for the data set of the second survey).
Address the following:
· Present the BIMS situation as an overview—problem, purpose, research questions, and hypotheses.
· Describe the instrument used for data collection.
· Identify types of data collected—quantitative, qualitative, or both—and how the data is collected.
· Identify the level of measurement for each of the variables involved in the study.
· Code the data if you have not done so. Describe how the data is coded and evaluate the procedure used.
· Clean the data by eliminating the data input errors made.
· Draw conclusions about appropriateness of the data to meet the purpose of the study.
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