4-3 PROJECT ONE SUBMISSION

4-3 Project One Submission - Statistics
PLACE ORDER
Competencies In this project, you will demonstrate your mastery of the following competencies: Apply statistical techniques to address research      problems Perform regression analysis to address an authentic      problem Overview The purpose of this project is to have you complete all of the steps of a real-world linear regression research project starting with developing a research question, then completing a comprehensive statistical analysis, and ending with summarizing your research conclusions. Scenario You have been hired by the D. M. Pan National Real Estate Company to develop a model to predict median housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the median housing prices based square footage. To complete this task, use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided. Directions Using the Project One Template located in the What to Submit section, generate a report including your tables and graphs to determine if the square footage of a house is a good indicator for what the listing price should be. Reference the National Statistics and Graphs document for national comparisons and the Real Estate County Data spreadsheet (both found in the Supporting Materials section) for your statistical analysis. Note: Present your data in a clearly labeled table and using clearly labeled graphs. Specifically, include the following in your report: Introduction A. Describe the report: Give a brief description of the purpose of your report. a. Define the question your report is trying to answer. b. Explain when using linear regression is most appropriate. i. When using linear regression, what would you expect the scatterplot to look like? c. Explain the difference between response and predictor variables in a linear regression to justify the selection of variables. Data Collection A. Sampling the data: Select a random sample of 50 counties. a. Identify your response and predictor variables. B. Scatterplot: Create a scatterplot of your response and predictor variables to ensure they are appropriate for developing a linear model. Data Analysis A. Histogram: For your two variables, create histograms. B. Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation. C. Interpret the graphs and statistics: a. Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables. b. Compare and contrast the shape, center, spread, and any unusual characteristic for your sample of house sales with the national population. Is your sample representative of national housing market sales? Develop Your Regression Model A. Scatterplot: Provide a graph of the scatterplot of the data with a line of best fit. a. Explain if a regression model is appropriate to develop based on your scatterplot. B. Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model. b. Identify any possible outliers or influential points and discuss their effect on the correlation. c. Discuss keeping or removing outlier data points and what impact your decision would have on your model. C. Find r: Find the correlation coefficient (r). b. Explain how the r value you calculated supports what you noticed in your scatterplot. Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model. A. Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables. B. Interpret regression equation: Interpret the slope and intercept in context. C. Strength of the equation: Provide and interpret R-squared. a. Determine the strength of the linear regression equation you developed. D. Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the square footage of your home. Conclusions A. Summarize findings: In one paragraph, summarize your findings in clear and concise plain language for the CEO to understand. Summarize your results. a. Did you see the results you expected, or was anything different from your expectations or experiences? i. What changes could support different results, or help to solve a different problem? ii. Provide at least one question that would be interesting for follow-up research. What to Submit To complete this project, you must submit the following: Project One Template: Use this template to structure your report, and submit the finished version as a Word document. Supporting Materials The following resources may help support your work on the project: Document: National Statistics and Graphs Use this data for input in your project report. Spreadsheet: Real Estate County Data Use this data for input in your project report. Tutorial: Downloading Office 365 Programs Use this tutorial for support with Office 365 programs. Use these tutorials for support with the Excel functions you will use in the project:Median Housing Price Model for D. M. Pan National Real Estate Company 3 [Note: To complete this template, replace the bracketed text with your own content. Remove this note before you submit your outline.] Report: Median Housing Price Prediction Model for D. M. Pan National Real Estate Company [Your Name] Median Housing Price Prediction Model for D. M. Pan National Real Estate Company 1 Southern New Hampshire University Introduction [Describe the report: Include in this section a brief overview, including the purpose of the report and your approach.] Data Collection [Sampling the data: Outline how you obtained your sample data, including the response and predictor variables.] [Scatterplot: Insert a correctly labeled scatterplot of your chosen variables.] Data Analysis [Describe your study briefly. Discuss the requirements of the data sets for a linear regression. Explain the difference between response and predictor variables in a linear regression to justify the selection of variables.] [Histogram: Insert the histogram of the two variables. Be sure to include appropriate labels.] [Summary statistics: Insert a table to show the summary statistics.] [Interpret the graphs and statistics: Describe the shape, center, spread, and any unusual characteristic (outliers, gaps, etc.) and what they mean based on your sample data and the graphs you created.] [Explain how these characteristics of the sample data compare to the same characteristics of the national population. Also, determine whether your sample is representative of the national housing market sales.] The Regression Model [Scatterplot: Include the scatterplot graph of the sample with a line of best fit.] [Based on your graph, explain whether a regression model can be developed for the data and how.] [Discuss associations: Explain the associations in the scatterplot, including the direction, strength, form in the context of your model.] [Find r: Calculate the correlation coefficient and explain how it aligns with your interpretation of the data from the scatterplot.] The Line of Best Fit [Regression equation: Insert the regression equation.] [Interpret regression equation: Interpret the slope and intercept in context.] [Strength of the equation: Interpret the strength of the regression equation, R-squared.] [Use regression equation to make predictions: Use the regression equation to make a sample prediction.] Conclusions [Summarize findings: Summarize your findings in clear and concise plain language. Outline any questions arising from the study that might be interesting for follow-up research.]New England House Listing Price Data by Region Source: https://www.realtor.com/research/data/ Regional sample (n = 1000) State County Region House listing price Cost per square foot Square footage CT litchfield New England $329,050 $153 1,888 ME penobscot New England $169,500 $103 1,586 NH merrimack New England $299,950 $145 2,152 VT washington New England $289,950 $141 1,959 ME york New England $391,550 $230 1,719 VT washington New England $222,500 $135 1,670 NH strafford New England $311,471 $166 1,885 MA suffolk New England $699,050 $647 1,259 MA norfolk New England $642,500 $309 2,210 NH hillsborough New England $339,950 $164 2,090 RI washington New England $499,050 $259 1,871 NH belknap New England $289,950 $156 1,869 VT rutland New England $228,800 $117 1,993 RI newport New England $579,050 $292 2,128 MA franklin New England $230,050 $133 1,800 ME penobscot New England $157,050 $94 1,600 VT washington New England $300,050 $154 1,896 MA berkshire New England $379,950 $185 2,032 ME kennebec New England $187,050 $104 1,695 NH cheshire New England $266,550 $132 1,981 VT franklin New England $219,950 $120 1,750 CT new london New England $290,000 $153 1,848 NH merrimack New England $314,950 $146 2,174 NH merrimack New England $299,950 $140 2,176 NH hillsborough New England $358,950 $173 2,036 CT windham New England $204,000 $123 1,615 VT washington New England $295,050 $147 1,888 CT new london New England $268,500 $159 1,648 CT new haven New England $279,950 $158 1,724 MA plymouth New England $491,550 $244 2,028 MA franklin New England $223,800 $135 1,780 NH cheshire New England $260,500 $131 1,838 CT new haven New England $279,050 $153 1,790 ME penobscot New England $159,750 $100 1,588 NH grafton New England $259,300 $150 1,840 VT washington New England $299,050 $147 1,850 ME york New England $339,050 $205 1,772 CT new haven New England $272,421 $150 1,763 MA suffolk New England $764,050 $669 1,341 NH grafton New England $253,850 $143 1,741 RI newport New England $598,050 $292 2,170 MA middlesex New England $655,000 $276 2,400 MA franklin New England $299,050 $150 1,960 CT new london New England $274,950 $121 1,212 RI providence New England $279,050 $185 1,504 MA barnstable New England $599,950 $318 1,920 CT litchfield New England $398,050 $172 2,268 NH belknap New England $295,000 $162 1,838 NH belknap New England $269,950 $153 1,797 MA suffolk New England $799,050 $708 1,311 RI kent New England $275,050 $177 1,524 CT new haven New England $258,500 $146 1,410 VT windsor New England $349,050 $158 2,120 CT litchfield New England $329,950 $150 1,776 NH cheshire New England $234,550 $123 1,845 NH cheshire New England $258,864 $126 1,968 NH hillsborough New England $341,444 $160 2,126 RI washington New England $489,950 $253 1,812 CT middlesex New England $342,450 $170 1,874 CT new london New England $294,050 $154 1,8project 1 data Real Estate County Data for 2019 Source: https://www.realtor.com/research/data/ 2019 County Data (n=978) Excel Filename created: RDC_Inventory_Core_Metrics_County_History.csv County level measures are based on averages Region State County median listing price median $s per square foot median square feet East North Central il adams $135,215 $88 1598 East North Central il champaign $191,054 $107 1760 East North Central il coles $93,141 $65 1591 East North Central il cook $314,629 $166 1442 East North Central il dekalb $210,494 $108 1844 East North Central il dupage $412,547 $181 2203 East North Central il grundy $254,322 $118 1936 East North Central il henry $110,053 $69 1449 East North Central il jackson $99,574 $64 1620 East North Central il kane $321,961 $136 2329 East North Central il kankakee $151,231 $96 1577 East North Central il kendall $266,967 $119 2140 East North Central il knox $106,418 $67 1590 East North Central il la salle $127,516 $84 1482 East North Central il lake $408,310 $159 2529 East North Central il macon $106,893 $61 1749 East North Central il macoupin $94,494 $64 1494 East North Central il madison $128,071 $82 1591 East North Central il mchenry $279,481 $124 2173 East North Central il mclean $157,728 $89 1780 East North Central il ogle $178,639 $90 1867 East North Central il peoria $127,413 $71 1811 East North Central il rock island $121,610 $88 1440 East North Central il sangamon $145,027 $81 1781 East North Central il st. clair $156,788 $82 1767 East North Central il stephenson $106,561 $60 1704 East North Central il tazewell $138,981 $78 1803 East North Central il vermilion $78,821 $54 1577 East North Central il whiteside $103,858 $71 1457 East North Central il will $289,846 $132 2181 East North Central il williamson $130,832 $76 1651 East North Central il winnebago $133,320 $76 1676 East North Central in allen $212,572 $98 1927 East North Central in bartholomew $280,054 $101 2712 East North Central in boone $448,568 $118 3700 East North Central in clark $249,307 $121 1876 East North Central in dearborn $220,555 $95 1778 East North Central in delaware $107,724 $69 1540 East North Central in elkhart $198,174 $92 2117 East North Central in floyd $232,319 $105 2098 East North Central in grant $75,309 $53 1510 East North Central in hamilton $378,444 $115 3483 East North Central in hancock $322,137 $106 3098 East North Central in hendricks $290,093 $108 2662 East North Central in henry $83,253 $57 1545 East North Central in howard $124,139 $77 1571 East North Central in johnson $274,236 $106 2641 East North Central in kosciusko $252,047 $131 1864 East North Central in la porte $251,713 $114 1898 East North Central in lake $215,915 $111 1902 East North Central in lawrence $155,672 $87 1745 East North Central in madison $105,965 $63 1709 East North Central in marion $210,745 $96 2
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Develop a community-wide intervention to reduce elevated blood pressure and hypertension in the State of Alabama that in in body of the report Conclusions References (8 References Minimum) *** Words count = 2000 words. *** In-Text Citations and References using Harvard style. *** In Task section I’ve chose (Economic issues in overseas contracting)" Electromagnetism w or quality improvement; it was just all part of good nursing care.  The goal for quality improvement is to monitor patient outcomes using statistics for comparison to standards of care for different diseases e a 1 to 2 slide Microsoft PowerPoint presentation on the different models of case management.  Include speaker notes... .....Describe three different models of case management. visual representations of information. They can include numbers SSAY ame workbook for all 3 milestones. You do not need to download a new copy for Milestones 2 or 3. 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Throughout your nurse practitioner program Vignette Understanding Gender Fluidity Providing Inclusive Quality Care Affirming Clinical Encounters Conclusion References Nurse Practitioner Knowledge Mechanics and word limit is unit as a guide only. The assessment may be re-attempted on two further occasions (maximum three attempts in total). All assessments must be resubmitted 3 days within receiving your unsatisfactory grade. You must clearly indicate “Re-su Trigonometry Article writing Other 5. June 29 After the components sending to the manufacturing house 1. In 1972 the Furman v. Georgia case resulted in a decision that would put action into motion. Furman was originally sentenced to death because of a murder he committed in Georgia but the court debated whether or not this was a violation of his 8th amend One of the first conflicts that would need to be investigated would be whether the human service professional followed the responsibility to client ethical standard.  While developing a relationship with client it is important to clarify that if danger or Ethical behavior is a critical topic in the workplace because the impact of it can make or break a business No matter which type of health care organization With a direct sale During the pandemic Computers are being used to monitor the spread of outbreaks in different areas of the world and with this record 3. Furman v. Georgia is a U.S Supreme Court case that resolves around the Eighth Amendments ban on cruel and unsual punishment in death penalty cases. The Furman v. Georgia case was based on Furman being convicted of murder in Georgia. Furman was caught i One major ethical conflict that may arise in my investigation is the Responsibility to Client in both Standard 3 and Standard 4 of the Ethical Standards for Human Service Professionals (2015).  Making sure we do not disclose information without consent ev 4. Identify two examples of real world problems that you have observed in your personal Summary & Evaluation: Reference & 188. Academic Search Ultimate Ethics We can mention at least one example of how the violation of ethical standards can be prevented. Many organizations promote ethical self-regulation by creating moral codes to help direct their business activities *DDB is used for the first three years For example The inbound logistics for William Instrument refer to purchase components from various electronic firms. During the purchase process William need to consider the quality and price of the components. In this case 4. A U.S. Supreme Court case known as Furman v. Georgia (1972) is a landmark case that involved Eighth Amendment’s ban of unusual and cruel punishment in death penalty cases (Furman v. Georgia (1972) With covid coming into place In my opinion with Not necessarily all home buyers are the same! When you choose to work with we buy ugly houses Baltimore & nationwide USA The ability to view ourselves from an unbiased perspective allows us to critically assess our personal strengths and weaknesses. This is an important step in the process of finding the right resources for our personal learning style. Ego and pride can be · By Day 1 of this week While you must form your answers to the questions below from our assigned reading material CliftonLarsonAllen LLP (2013) 5 The family dynamic is awkward at first since the most outgoing and straight forward person in the family in Linda Urien The most important benefit of my statistical analysis would be the accuracy with which I interpret the data. 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