Six months ago, large amounts of funds were allocated to temporary shelters for people who are homeless in your county. However, a recent county data report indicated that people who are homeless are still sleeping in their cars or in parks. You are the lead researcher in the county’s office and are aware that the question calls for qualitative research methodology. You are tasked with exploring and understanding the barriers that will lead to more effective policy outcomes. Would the data analysis inherent in a qualitative descriptive design effectively address the questions? Explain.
Tag: Data Analysis
Data Analysis
What were some of the findings, for example, if there were any hypotheses asked, were they supported?
Data analysis
• Respond to the exam items below.
• Data analysis is required.
- Use the attached Excel files to complete the analysis.
• Answer all questions in two pages or less, in a Word document.
• When graphs are required, make them in Excel and then paste them into the Word document.
Each item is worth 25 pts:
1) Question:
a. In a paragraph, explain what Business Analytics is, give real-world examples.
b. In a paragraph, explain what Lifetime Value of a Customer is (LTV) and how it is used in CRM.
2) Open the MakeupSales file:
a. Clean the file. It is the policy of management to remove any observation that contains an error or is missing data, even one datum. How many observations remain in the cleaned file?
b. Who is the leading sales rep in sales revenue? Who is the weakest?
c. What product line generates the most sales revenue? What line is the weakest?
d. Which is the strongest sales region (east, midwest, south, west)?
e. Use professional quality graphs with discussion for b, c, and, d.
3) Question:
In two paragraphs, explain Relational Databases and Non-Databases (this would include definitions of both as well as discussion on database design, types of data, how they are different).
4) Open the Cereal Cluster file:
a. Assume the file has been cleaned.
b. Run a cluster analysis in Excel using k-means, presume 3 clusters.
c. Choose 3 variables to use in discerning cluster membership.
d. When you find your 3 clusters, investigate them quantitatively and compare the clusters on the variables you chose.
e. Use a professional quality graph and table for d and include discussion.
DATA ANALYSIS
CATEGORICAL DATA ANALYSIS
Create a research question using the General Social Survey dataset that can be answered using categorical analysis.
RESOURCES: Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero
Use SPSS to answer the research question. Post your response to the following:
(1) Include the General Social Survey Dataset’s mean of Age to verify the dataset you used.
(2) What is your research question?
(3) What is the null hypothesis for your question?
(4) What research design would align with this question?
(5) What dependent variable was used and how is it measured?
(6) What independent variable is used and how is it measured?
(7) If you found significance, what is the strength of the effect?
(8) Explain your results for a lay audience and further explain what the answer is to your research question.
Be sure to support your output and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style
Data analysis
Activity I – You have just opened a restaurant in a large city, and you are deciding what you should charge for a regular-sized soda. You’d like to charge a price equal to the average of your competitors, which you believe is $2.58. To inform your decision, you want to learn more about the average price charged by competing restaurants in the area. You know you won’t be able to get prices for every restaurant, so you randomly sample 35 and collect their soda prices. These data are in Soda.xlsx ( See the attached)
You are assuming the mean soda price is $2.58 for all of your competitors. When conducting data analysis to test this belief, what is this assumption called?
Calculate the t-statistic assuming the mean soda price for all of your competitors is $2.58.
Calculate the p-value for your t-statistic.
Using a confidence level of 90%, test whether the mean soda price of all your competitors is $2.58 using the t-stat.
Using a confidence level of 90%, test whether the mean soda price of all your competitors is $2.58 using the p-value.
Is it possible that your answers to parts d and e would yield different conclusions?
Activity II – To better assess your willingness-to-pay for advertising on others’ websites, you want to learn the mean profit per visit for all visits to your website. To accomplish this, you have collected a random sample of 4,738 visits to your website over the past six months. This sample includes information on visit duration and profits. The data are contained in WebProfits.xlsx (See the attached). Using the data in WebProfits.xlsx:
Build a 99% confidence interval for the mean profit per visit for all of your visitors.
Let the null hypothesis be that mean profit per visit for all of your visitors is $11.50.
Calculate the corresponding t-stat for this null hypothesis.
Calculate the corresponding p-value for this null hypothesis.
With strength of 95%, decide whether or not to reject this null hypothesis.
Detail the reasoning behind your decision.
Data analysis
Write a 2- to 3-page methodology section of your research report. The methodology section should expand on the work you began last week in your learning team. You revise and improve the draft you submit this week for your final Course Capstone Project submission. Your methodology section must contain the following subsections:
Subjects: Who was studied? What are the characteristics of the population samples (e.g., age, sex, race, socio-economic status, etc.)? How were the sample subjects selected? Address validity requirements (i.e., appropriate sample sizes, appropriate causal relationships among variables, etc.). Provide clear rationale for how and why sample subjects were chosen.
Data collection: Describe how sample data was collected and organized. Was the data quantitative or categorical or both? Describe how each variable was measured and how data reliability was ensured.
Data analysis: Describe the data in terms of population parameters (i.e., means, medians, standard deviations, etc.), and describe which statistical methods were used (i.e., ANOVA, linear regression, t-test, chi-square, etc.) to analyze the data.
Results: Interpret the results of the statistical analyses suitable for presentation to stakeholders who may not understand statistical terminology.
Conclusion: Describe the outcomes suggested by the data. Describe the strengths and limitations of the analyses.
Format your assignment according to APA guidelines.
Submit the methodology section in a Word document using the following instructions.
Data Analysis
A4 size, Include the R coding, and follow the instructions in the question paper, thanks! 😀
R data & question paper:
https://drive.google.com/drive/u/0/folders/1MCzTUzamnIOyMG1kl_6dy-fHtXzvNWtf
Data Analysis
https://filetransfer.io/data-package/g1nUyLCd#linkhttps://filetransfer.io/data-package/g3RxjrOG#link
Data Analysis
Let’s say you own an online T-shirt store. You offer three sizes (small, medium and large) and 10 different colors. Customers can choose what images to print on their T-shirts from a database of 200 pictures. You want to employ a push/pull combined supply chain model. What would be your answers to the following questions?
Where shall be the push/pull boundary (i.e., decoupling point) on your supply chain? Why? (6 points)
Discuss the benefit of employing a push/pull combined supply chain model for your online T-shirt store. Would it be better than a push or a pure pull model for your business? Why? (6 points)
Data Analysis
Required analysis program: Analysis ToolPak – for all analyses in this class (RStudio or R Programming for BONUS point seekers only – 10 bonus points if used for analysis).
Author, Hossein Zare, PhD
Citation: Zare, H. (2017). HMGT 400 Research and Data Analysis in Health Care-Exercise. UMGC.EDU
Exercise # 1 Instructions:
1. You may download the dataset from the link below. This dataset provides information about hospitals in 2011 and 2012. Before you do that however consult the additional instructions that I provided to you in 4 PDF email attachments. ([a]. Ex 1 – Additional Instructions. [b] Ex 1 – Instructions t-Test to compare means [c] Ex 1 – Example t-Test Output. [d] Ex 1 – Example Output – Graphs).
2. Analyze the data, using these instructions. Your objective is to use the results of your analysis to create “summary statistics” (Count (N), Mean, and Standard Deviation) for each hospital characteristic and each year (2011 and 2012) and complete Table 1 (template below). You should then create any meaningful graphs (using Excel) to summarize your findings and to write a short paragraph summary report describing your findings.
3. Your report may be in WORD format, with the tables you create in Excel copied and pasted in WORD. Submit your report to the appropriate folder.
Table 1. Descriptive statistics between hospitals in 2011 & 2012