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Data, Statistics, and Decisions in Business You have been

Resolved Question:

Data, Statistics, and Decisions in Business

You have been recently employed as the director of operations of a hotel. The hotel is in a relatively large city with many other comparable hotels in its vicinity. As part of your job, your responsibilities include:

Establishing a sound data and information infrastructure to support ongoing hotel operations. Determining what data you should collect on an ongoing basis and how you should use that data to make effective decisions aimed at balancing high occupancy with high per-room profitability Determining what information you will need to be able to effectively market your hotel Establishing a basic monthly reporting infrastructure that will enable you to keep track of the key performance metrics Create a Microsoft Word document listing three different operational functions for your hotel. Examples of hotel functions include setting daily room rates, attracting events (meetings, conferences, etc.), managing hotel material, etc. For each function, specify what data you would need to help you manage the function better, how you would analyze the data (using one or more of the descriptive techniques), what type of data individual variables represent (e.g., interval), and how you would tabulate or graph the data you collected for each function. For example, to set daily room prices, you can use historical sales data to compute average daily prices, a measure of dispersion to estimate up-and-down volatility, and histograms to graphically illustrate occupancy rates associated with different price levels.

Your description of each of the three operational functions should include a clear specification of the function (e.g., setting daily room prices), a description of the data source (e.g., historical sales data), the data type, a specific descriptive technique to convert data into information pertinent to each function, and a description of tabular and graphical results, including examples generated using a Microsoft Excel spreadsheet. can you help with this question i need it today

During this course, you will analyze data, develop your own hypothesis, test it, and write a structured APA report using the dataset provided below. The project will be based on conducting an independent analysis of an adequately set-up database.

Here's what you will do each week to accomplish your goals:

Week 1: You will derive analytical results that describe the characteristics of the data-discrete and continuous.

Week 2: You will derive analytical results based on continuous variables and compute the mean, median, variance, standard deviation, and range.

Week 3: You will derive analytical results based on dichotomous variables.

Week 4: You will derive analytical results and formulate three different hypotheses to test.

Week 5: You will derive analytical findings based on a single continuous variable.

Week 6: You will provide a summary of the empirical analyses you conducted during the course of the past five weeks in terms of the specific insights you gained.

Your final project entails systematic extraction of decision-aiding insights out of a dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area. This project will provide you with hands-on experience in conducting and interpreting different types of function-wise statistical analysis. The focus of your analysis will be on marketing strategies and analysis-related topics. At times, you will be expected to conduct additional research on topics that are not adequately covered in your text, for example, data due diligence.

The first step in any data analytical undertaking is to conduct basic data due diligence, the focus of which is on assessing the scope and limitations of your data. This is an important step as virtually all business data contains some degree of imperfection, such as missing values, miscoded variables, or nonsensical values (such as a person being five hundred years old). Beyond looking for flaws in data, data due diligence also entails describing the basic characteristics of data, such as the number of variables, number of cases, ranges of values of individual variables, variable types, etc.

This week, as the first step in your data analytical project, you will put together a step-by-step outline of the data due diligence process that you would follow and provide a rationale for each step in your process.

Submit your response in a 2- to 3-page Microsoft Word document to the W1

can you help with this question as well if you need additional information about question i can post i need week one today then all the anwer each week one after next

Customer:replied 3 years ago.

this one is due thursday

Investigate How a Company Uses Data in Marketing

Select a company (maybe your employer) and assess how it uses data in marketing its products or services. (If it is not your employer, find a sizable local company or search the Internet for a company and contact the marketing department.) Specifically, address the following considerations:

What data does the company capture and have available?

What additional data does the company acquire from outside data vendors and why?

What specific insights or information do companies hope to extract from the available data?

How does the analysis of the data translate into decisions?

Submit your answers in a 4- to 5-page Microsoft Word document.

Name your document SU_MBA5008_W2_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, September 22,

Customer:replied 3 years ago.

These are all my final project question and due dates for each week can you help me

Assignment 4: Final Project

During this course, you will analyze data, develop your own hypothesis, test it, and write a structured APA report using the dataset provided below. The project will be based on conducting an independent analysis of an adequately set-up database.

Here's what you will do each week to accomplish your goals:

Week 1: You will derive analytical results that describe the characteristics of the data-discrete and continuous.

Week 2: You will derive analytical results based on continuous variables and compute the mean, median, variance, standard deviation, and range.

Week 3: You will derive analytical results based on dichotomous variables.

Week 4: You will derive analytical results and formulate three different hypotheses to test.

Week 5: You will derive analytical findings based on a single continuous variable.

Week 6: You will provide a summary of the empirical analyses you conducted during the course of the past five weeks in terms of the specific insights you gained.

Week 1 Your final project entails systematic extraction of decision-aiding insights out of a dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area. This project will provide you with hands-on experience in conducting and interpreting different types of function-wise statistical analysis. The focus of your analysis will be on marketing strategies and analysis-related topics. At times, you will be expected to conduct additional research on topics that are not adequately covered in your text, for example, data due diligence.

The first step in any data analytical undertaking is to conduct basic data due diligence, the focus of which is on assessing the scope and limitations of your data. This is an important step as virtually all business data contains some degree of imperfection, such as missing values, miscoded variables, or nonsensical values (such as a person being five hundred years old). Beyond looking for flaws in data, data due diligence also entails describing the basic characteristics of data, such as the number of variables, number of cases, ranges of values of individual variables, variable types, etc.

This week, as the first step in your data analytical project, you will put together a step-by-step outline of the data due diligence process that you would follow and provide a rationale for each step in your process.

Submit your response in a 2- to 3-page Microsoft Word document to the W1: Assignment 4 Dropbox by Saturday, September 17, Assignment 4: Final Project

Probability and Hypothesis Testing

Week 2 Your final project entails systematic extraction of decision-aiding insights from a dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area. The goal of this project is to provide you with hands-on experience in conducting and interpreting different types of function-wise statistical analysis. The focus of your analysis will be on the marketing strategy and analysis-related topics. At times, you will be expected to conduct additional research on topics that are not adequately covered in your text, for example, data due diligence.

In this segment, you will estimate simple probability and test hypotheses using the provided SampleDataSet.

Probability: Find the Region variable in the SampleDataSet. Using SampleDataSet, create a frequency distribution or a histogram. Based on the frequency distribution or histogram, estimate the probability associated with each region.

Test the following hypotheses:

1. Hypothesis 1: Age (of residents) of Region 1 > Age of Region 7

2. Hypothesis 2: Wealth score of mail donors ≥ Wealth score of mail nondonors

Specify your hypothesis completely in terms of null and alternative; detail your findings and conclusions.

Submit your answers in a 3- to 4-page Microsoft Word document.

Name your document: SU_MBA5008_W2_A4_LastName_FirstInitial.doc.

Submit your document to the W2: Assignment 4 Dropbox by Sunday, September 25, href="http://www.justanswer.com/homework/5kiiq-data-statistics-decisions-business-you.html1.

Assignment 4: Final Project

Estimation

Week 3 Your final project entails systematic extraction of decision-aiding insights out of a dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area.

In this section, you will carry out the following basic estimation and tests of differences using the provided SampleDataSet.xlsx:

1. Identify three continuous and three discrete variables and describe their distribution numerically (e.g., central tendency, spread) as well as graphically. Compare the results.

2. Using the variables selected, conduct all possible t-tests and chi-squared tests. Describe your findings.

In addition, discuss how data limitations (e.g., missing values, etc.) can affect the validity and reliability of statistical estimations and tests of differences. Be specific. Show your work using Microsoft Excel and import your work into a Microsoft Word document.

Submit your response with imported Microsoft Excel work in a 3- to 4-page Microsoft Word document.

Name your document SU_MBA5008_W3_A4_LastName_FirstInitial.doc.

Submit your document to the W3: Assignment 4 Dropbox by Sunday, October 2, href="http://www.justanswer.com/homework/5kiiq-data-statistics-decisions-business-you.html1.

Assignment 4: Final Project

Ongoing Data Exploration

Week 4 Your final project entails systematic extraction of decision-aiding insights from a dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area. The goal of this project is to provide you with hands-on experience in conducting and interpreting different types of statistical analysis. The focus of your analysis will be on marketing strategies and analysis-related topics. At times, you will be expected to conduct additional research on topics that are not adequately covered in your text, for example, data due diligence.

In this section, you will conduct correlation and regression analyses using the provided SampleDataSet.xlsx.

Correlation: Compute a correlation matrix that includes all continuous variables. Identify all individual correlations that are significant at the 95 percent level.

Regression: Build a multiple regression model to explain the variability in the median school year. Describe the goodness of fit of your model and summarize your findings. Select at least four to seven similar independent variables from the remaining forty-nine measures and justify your selection.

Submit your response in Microsoft Excel.

Name your worksheet SU_MBA5008_W4_A4_LastName_FirstInitial.xls.

Submit your worksheet to the W4: Assignment 4 Dropbox by Sunday, October 9, href="http://www.justanswer.com/homework/5kiiq-data-statistics-decisions-business-you.html1.

Assignment 4: Final Project

Week 5 Ongoing Data Exploration

Your final project entails systematic extraction of decision-aiding insights from a dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area. The goal of this project is to provide you with hands-on experience in conducting and interpreting different types of statistical analysis. The focus of your analysis will be on marketing strategies and analysis-related topics. At times, you will be expected to conduct additional research on topics that are not adequately covered in your text, for example, data due diligence.

In the Week 4 assignment, you were asked to build a multiple regression model to explain the variability in the median school year, using a minimum of seven independent variables. Using the same model, thoroughly assess your model's diagnostics. Identify all relevant assessment dimensions, briefly outline their purpose and importance, and provide an assessment of your model in terms of the identified diagnostic measures.

Submit your response in a 2- to 3-page Microsoft Word document to the W5: Assignment 4 Dropbox by Sunday, October 16, href="http://www.justanswer.com/homework/5kiiq-data-statistics-decisions-business-you.html1

Assignment 3: Final Project

Week 6 In the previous weeks, you used the sample dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area so as to conduct various analyses. This is similar to providing business analytics support on an ongoing basis and entails answering (by means of analysis) many different questions.

Summarize your findings and draw conclusions. Create a final report document containing the following:

Executive summary: This section should be a 1-page summary of the most important findings presented in the context of the recommended course of action.

Data and methodology: In this section, describe the characteristics of the data and the specific methodologies used in the analysis.

Analytic details: This section should contain supporting evidence for the findings and conclusions presented in the executive summary section.

Create your report in a 3- to 4-page Microsoft Word document.

Name your report SU_MBA5008_W6_A3_LastName_FirstInitial.doc.

Submit your report to the W6: Assignment 3 Dropbox by Wednesday, October 19,

I'm familiar with the topics, but the final project is very exhaustive. I'd tell you later if I could work on this as well. Working on your present assignment for now.

i only need final questions answered by dues date and midweek by due dates. this will be all question for the whole course.

These are all of my midweek questions and numerials question and due dates can you do these questions and post in a separate thead so I can pay you separate for each question this is law and ethics class I need your help for these questions and the other final question I post in the previous reply

Week 2 question1 Investigate How a Company Uses Data in Marketing

Select a company (maybe your employer) and assess how it uses data in marketing its products or services. (If it is not your employer, find a sizable local company or search the Internet for a company and contact the marketing department.) Specifically, address the following considerations:

What data does the company capture and have available?

What additional data does the company acquire from outside data vendors and why?

What specific insights or information do companies hope to extract from the available data?

How does the analysis of the data translate into decisions?

Submit your answers in a 4- to 5-page Microsoft Word document.

Name your document SU_MBA5008_W2_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, September 22, 2011.

Week 2 question 2 Hands-On Analysis

Select one of the datasets included with your textbook (on a CD). Open the selected data file in Microsoft Excel software; choose three continuous and two discrete measures and perform the following:

For the continuous variables, compute all available measures of central tendency, range, and dispersion; display your results numerically and graphically. Describe the distribution of each variable. Which variable exhibits the greatest amount of variability? What is the basis of your ate lconclusion?

For each of the two discrete variables, compute all applicable descriptive measures; show your results numerically and graphically. Compare and contrast the two variables in terms of the measures you computed.

Submit your answers in a 4- to 5-page Microsoft Word document.

Name your document SU_MBA5008_W2_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, September 22, 2011.

Week 3 question 3 Parameter Estimation, Inferences, and Tests of Difference

You are a marketing analyst in a large grocery store chain. Your job entails developing a robust customer knowledge base utilizing the company's vast database of in-store purchases. To date, you have been able to build a profile of your customer base, draw inferences about different customer groupings, and compare customer behaviors across the different sales regions. Your task is to:

Describe the business benefits of parameter estimation. Provide examples of the type of parameters that might be of interest to decision makers in areas such as marketing.

Elaborate on how being able to estimate those parameters would benefit the quality of the resultant decisions.

Describe the business benefits of drawing inferences-specifically, when it is advantageous to rely on inferences and what is required to ascertain the correctness of inferences.

Discuss the relationship between tests of difference and hypothesis testing in the context of designing marketing promotions.

Submit your answers in a 2- to 3-page Microsoft Word document.

Name your document SU_MBA5008_W3_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, September 29, 2011.

Week 3 question 4 Type I vs. Type II error

You are a business analyst employed by a large database management and consulting organization. Your job entails analysis of the available data that tends to vary considerably across clients in terms of volume and quality, with the goal of previously unknown insights or validating currently-held beliefs. One of your concerns is the validity and reliability of your conclusions; hence you are always careful about Type I and Type II errors.

Discuss the differences between Type I and Type II errors in the context of business decision making. Explain how each of the two types of errors can impact both, the validity as well as the reliability of conclusions? As a business analyst, what would you do to minimize the chances of either Type I or Type II errors adversely impacting your conclusions?

Submit your answers in a 2- to 3-page Microsoft Word document.

Name your document: SU_MBA5008_W3_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, September 29, 2011.

Week 4 question 5 Regression Modeling

Using the XR17-07 dataset (in the data sets/Excel files directory of the CD accompanying your textbook) and Microsoft Excel, build and validate a multiple regression model. Explicitly describe the following:

Choose the dependent as well as the independent variables. Why do you think are the selected independent variables expected to cause changes in the dependent variables?

Assess the goodness of fit of your model.

Interpret the coefficients of the regression model. Which independent variable has the strongest impact on the dependent variables? Which independent variable has the weakest impact?

Summarize the key business takeaways from your model. Briefly describe what the model communicates.

Submit your response in a 2- to 3-page Microsoft Word document (copying any supporting parts of the Microsoft Excel output).

Name your document SU_MBA5008_W4_A2_LastName_FirstInitial.doc.

Submit your document to the W4: Assignment 2 Dropbox by Thursday, October 6, 2011.

Week4 question 6 Statistical vs. Practical Significance

In applied business analysis, there is a tendency to distinguish between statistical and practical significance. Consequently, the larger the sample size, the more sensitive the statistical significance test. As the sample size increases, even smaller differences become statistically significant. As a result, a business analyst might conclude that a particular result might be statistically but not practically significant.

Do you believe it is appropriate for business analysts to divide statistically significant results (such as coefficients in a regression model) into practically significant and not practically significant results (which should be, in effect, disregarded)? Why or why not?

Submit your response in a 1- to 2-page Microsoft Word document.

Name your document SU_MBA5008_W4_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, October 6, 2011.

Week 5 question 7 Assessing the Quality of Regression Results

Consider the following multiple regression results. Using a= .05 as the significance level, identify all statistically significant predictors. In a relative sense, which variable has the strongest impact? What is the interpretation of the "constant" term?

Independent Variables

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

(Constant)

.991

.106

9.362

.000

Variable 1

.045

.101

.015

.445

.657

Variable 2

-.051

.084

-.020

-.607

.544

Variable 3

.299

.107

.062

2.786

.005

Variable 4

-.341

.329

-.023

-1.039

.299

Variable 5

.000

.000

-.011

-.284

.776

Variable 6

.000

.000

.009

.251

.802

Variable 7

.000

.000

-.011

-.264

.792

Variable 8

.000

.000

-.001

-.022

.983

Variable 9

-.003

.005

-.015

-.704

.482

Variable 10

.031

.036

.019

.870

.384

Variable 11

-.023

.041

-.013

-.558

.577

Variable 12

-.001

.011

-.003

-.117

.907

Variable 13

.000

.000

.050

2.310

.021

Variable 14

.003

.000

.145

6.631

.000

Variable 15

.000

.000

-.008

-.380

.704

Variable 16

.053

.016

.075

3.403

.001

Variable 17

.006

.014

.430

.458

.647

Variable 18

-.006

.013

-.425

-.450

.653

Variable 19

-.136

.156

-.019

-.869

.385

Write your analysis in a 3- to 4-page Microsoft Word document.

Name your document SU_MBA5008_W5_A2_LastName_FirstInitial.doc.

Submit your analysis to the W5: Assignment 2 Dropbox by Thursday, October 13, 2011.

Week 5 question 8 Business Forecasting

From your textbook, Statistics for Management and Economics, complete the following exercises:

"Time Series Analysis and Forecasting": Exercises 20.47, 20.48, 20.49, 20.50, and 20.51

Submit your answers in a Microsoft Excel workbook, with each problem on a separate worksheet. Label each tab in the workbook with the exercise number. Highlight the answers in yellow and provide an interpretation in a text box.

Name your Microsoft Excel workbook SU_MBA5008_W5_A2_LastName_FirstInitial.xls.

Submit your workbook to the W5: Assignment 2 Dropbox by Thursday, October 13, 2011.

Customer:replied 3 years ago.

this is not law and ethics class but i meant quantative anylasis and decision making

how a re you comming along with question you are working on now?

can you do week 1 final assinment today it was due Saturaday 17, 2011 this will bring me current then my next qustions are due by thursday, midweek assignment Sept. 22, 2011. I will add Bonus to question but i can add bonus when i get money on my payroll card on thursday

Customer:replied 3 years ago.

1. ` Week 2 Due sept. 20 Question 1 You are a risk manager in a manufacturing company and one of your key responsibilities is securing of property insurance coverage to provide protection against damage caused by "acts of God," such as earthquakes, hurricanes, floods, etc. You begin the process with due diligence, which is focused on estimating the chances of a single "act of God" occurring in the year, as well as chances of two or more "acts of God" occurring in the year (also in the course of the subsequent year). Consider the different approaches to assigning probabilities to "acts of God." Which of the approaches will you be most inclined to choose and why? Which of those approaches will you be least inclined to choose and why?

Justify your answer with examples and reasoning. Comment on the postings and views of at least two peers.

2. Week 2 Due sept 20 Question 2 You are a marketing manager for a company that makes ready-to-eat breakfast cereals. Your company recently initiated a loyalty program for consumers, which resulted in a large purchaser database. The brand managers are eager to mine the available data, which they can use to design more effective promotional programs. Your first step is to conduct an exploratory baseline analysis, the goal of which is to describe the buyer base and estimate basic statistical descriptors of the said buyer base. You are particularly interested in the size of individual purchases, as well as the frequency of repurchases. Describe the individual statistics you would compute and discuss what would you learn from each statistic that would be of value in designing effective promotions.

Justify your answers with examples and reasoning. Comment on the postings of at least two peers.

3 week 3 Due sept 27 Question 3 You are a manager working for an insurance company. Your job entails processing individual claims filed by policyholders. In general, few claims are expensive. Each quarter, you compile a report summarizing key claim statistics, such as the number of claims submitted, the average cost per claim, and the total cost of submitted claims. In the last quarter's report, you notice a large difference between the mean and the median claim cost, the mean cost being much higher than the median cost. What do you attribute this difference to? Do you think the claims data is normally distributed? If so, why? If not, what distribution might best describe the data and why? Given the large difference between the two measures of central tendency, which of the two would you rely on in describing the average claim cost and why?

Justify your answers with examples and reasoning. Comment on the postings and views of at least two peers.

4. Week 3 Due sept 27 question4 You are a manager working for an insurance company. Your job entails processing individual claims filed by policyholders. In general, most claims are relatively minor, costwise, but a few are quite expensive. Each quarter, you compile a report summarizing key claims statistics that includes the number of claims submitted, the mean cost per claim, the median cost per claim, the proportion of claims being litigated, the number of emergency procedures, the proportion of men versus women, and the average age of claimants. Your measures are computed separately for the southern and northern regions, and you are interested in determining whether or not there are statistically significant differences between the two regions on each of the aforementioned measures. For which comparisons would you use the t-test and why? For which would you use the chi-squared test and why?

Justify your answers with examples and reasoning. Comment on the postings of at least two peers.

5. Week 4 Due oct 4 Question 5 One of the often-repeated mantras is "Correlation is not causation." What does this mean, and what is the significance of the expression for business analytics?

Justify your answers with examples and reasoning. Comment on the postings and views of at least two peers.

6 Week 4 Due oct 4 Question 6 Regression is one of the most widely used statistical techniques. In business, it is often used within the realm of what is known as predictive analytics-estimating the use of statistical techniques to estimate the likelihood or magnitude of future outcomes of interest. However, regression is also an explanatory tool because the regression model explains the variability in dependent variables with the help of one or more independent variables.

From the marketing management perspective, discuss regression as an explanatory and a predictive tool. What are the major differences between an explanatory and a predictive tool? In terms of the goodness of fit, what is the most important indicator of regression as an explanatory tool and as a predictive tool?

Justify your answers with examples and reasoning. Comment on the postings of at least two peers.

7 Due oct 11Week 5 question 7

You are a workers' compensation claims analyst working for a large manufacturing organization (worker's compensation is a worker injury protection; it pays medical and other expenses for workers who were injured on the job). A key part of your responsibilities is to "reserve" a certain amount of funds for each workers' compensation claim you process, which is necessary for making sure that each injury claim has adequate funds to pay its costs. This requires you to forecast, or estimate the expected future cost of each claim, which is both time-consuming and difficult, as there are multiple factors (such as the nature of injury, worker's age, the nature of accident, etc.) that determine the ultimate cost of individual claims. Having a lot of historical data (past claims), you decide to use regression analysis to help you forecast the expected cost of the individual workers' compensation claims.

Discuss how you would use regression to help you with your task-specifically, explain how you would go about evaluating the goodness-of-fit and the predictive efficacy of your model.

Justify your answers with examples and reasoning. Comment on the postings and views of at least two peers.

8. Due oct 11 Week 5 Question 8 In general, short-term forecasts are more accurate than long-term forecasts, as are forecasts where cyclical or seasonal factors are fairly well defined and repeatable. Describe the factors that influence the reliability of time-series forecasts. Under what circumstances would a time-series model offer a fairly reliable forecast?

Justify your answers with examples and reasoning. Comment on the postings of at least two peers.

9. Due oct 18 week 6 Question 9 As a marketing manager for a manufacturer of nonperishable products sold in grocery stores, you need to make various decisions. Identify three such decisions. Discuss how historical sales data, as well as promotional response data, can aid you in making these decisions.

Justify your answers with examples and reasoning. Comment on the postings and views of at least two peers.

10.Due oct 18 week 6Question 10

In the past several weeks, you have been introduced to a range of statistical data analysis tools. Consider what you have learned in the context of progression of data, information, and knowledge. What are the specific techniques you would consider most helpful in transforming information into knowledge (as opposed to just translating data into information)?

Justify your answer with examples and reasoning. Comment on the postings of at least two peers.

Please email the answer to me at cathey_marylin@yahoo. com for week two, three, four, five and 6 I already did week 1 two question for each week Due by Sept 20, sept 27, oct. 4 oct 11 and oct 18.

Customer:replied 3 years ago.

will you be able to help me with discussion question, midweek and final assignment i sent to you in reply box yesterday?

I can help only with selective parts, those involving only math or basic reasoning. If you send in only next one you'd be needing help with, I'd tell if I could assist.

Week 1 Your final project entails systematic extraction of decision-aiding insights out of a dataset (SampleDataSet.xlsx) provided to you in the Doc Sharing area. This project will provide you with hands-on experience in conducting and interpreting different types of function-wise statistical analysis. The focus of your analysis will be on marketing strategies and analysis-related topics. At times, you will be expected to conduct additional research on topics that are not adequately covered in your text, for example, data due diligence.

The first step in any data analytical undertaking is to conduct basic data due diligence, the focus of which is on assessing the scope and limitations of your data. This is an important step as virtually all business data contains some degree of imperfection, such as missing values, miscoded variables, or nonsensical values (such as a person being five hundred years old). Beyond looking for flaws in data, data due diligence also entails describing the basic characteristics of data, such as the number of variables, number of cases, ranges of values of individual variables, variable types, etc.

This week, as the first step in your data analytical project, you will put together a step-by-step outline of the data due diligence process that you would follow and provide a rationale for each step in your process.

also week 2 discussion question 1 and 2 due sept 17

Week 2 Due sept. 20 Question 1 You are a risk manager in a manufacturing company and one of your key responsibilities is securing of property insurance coverage to provide protection against damage caused by "acts of God," such as earthquakes, hurricanes, floods, etc. You begin the process with due diligence, which is focused on estimating the chances of a single "act of God" occurring in the year, as well as chances of two or more "acts of God" occurring in the year (also in the course of the subsequent year). Consider the different approaches to assigning probabilities to "acts of God." Which of the approaches will you be most inclined to choose and why? Which of those approaches will you be least inclined to choose and why?

Justify your answer with examples and reasoning. Comment on the postings and views of at least two peers.

2. Week 2 Due sept 20 Question 2 You are a marketing manager for a company that makes ready-to-eat breakfast cereals. Your company recently initiated a loyalty program for consumers, which resulted in a large purchaser database. The brand managers are eager to mine the available data, which they can use to design more effective promotional programs. Your first step is to conduct an exploratory baseline analysis, the goal of which is to describe the buyer base and estimate basic statistical descriptors of the said buyer base. You are particularly interested in the size of individual purchases, as well as the frequency of repurchases. Describe the individual statistics you would compute and discuss what would you learn from each statistic that would be of value in designing effective promotions.

Justify your answers with examples and reasoning. Comment on the postings of at least two peers.

then midweek question 1 & 2

Week 2 question1 Investigate How a Company Uses Data in Marketing

Select a company (maybe your employer) and assess how it uses data in marketing its products or services. (If it is not your employer, find a sizable local company or search the Internet for a company and contact the marketing department.) Specifically, address the following considerations:

What data does the company capture and have available?

What additional data does the company acquire from outside data vendors and why?

What specific insights or information do companies hope to extract from the available data?

How does the analysis of the data translate into decisions?

Submit your answers in a 4- to 5-page Microsoft Word document.

Name your document SU_MBA5008_W2_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, September 22, href="http://www.justanswer.com/homework/5kiiq-data-statistics-decisions-business-you.html1.

Week 2 question 2 Hands-On Analysis

Select one of the datasets included with your textbook (on a CD). Open the selected data file in Microsoft Excel software; choose three continuous and two discrete measures and perform the following:

For the continuous variables, compute all available measures of central tendency, range, and dispersion; display your results numerically and graphically. Describe the distribution of each variable. Which variable exhibits the greatest amount of variability? What is the basis of your ate lconclusion?

For each of the two discrete variables, compute all applicable descriptive measures; show your results numerically and graphically. Compare and contrast the two variables in terms of the measures you computed.

Submit your answers in a 4- to 5-page Microsoft Word document.

Name your document SU_MBA5008_W2_A2_LastName_FirstInitial.doc.

Submit your document to this Discussion Area by Thursday, September 22,

can you do these fist 3 question by today and 4, 5 by Thursday

Do you have dataset for week 1? I might help with above questions, except question 4 'Week 2 question1 Investigate How a Company Uses Data in Marketing.' For those worked out, I'll post the answers individually for each part here itself, then you could accept the answers paying same base price like last one for each answer.

But first I'd need datasets for 1)data due diligence, 3) Marketing manager breakfast cereals and 5) Week 2 question 2 Hands-On Analysis.

Select a company (maybe your employer) and assess how it uses data in marketing its products or services. (If it is not your employer, find a sizable local company or search the Internet for a company and contact the marketing department.) Specifically, address the following considerations:

What data does the company capture and have available?

What additional data does the company acquire from outside data vendors and why?

What specific insights or information do companies hope to extract from the available data?

How does the analysis of the data translate into decisions?

Submit your answers in a 4- to 5-page Microsoft Word document.

Name your documen

Submit your document to this Discussion Area by Thursday, September 22,

need these two midweek question by thursday sept 22

i don't need discussion questions any more just midweek and final question

Select a company (maybe your employer) and assess how it uses data in marketing its products or services. (If it is not your employer, find a sizable local company or search the Internet for a company and contact the marketing department.) Specifically, address the following considerations:

What data does the company capture and have available?

What additional data does the company acquire from outside data vendors and why?

What specific insights or information do companies hope to extract from the available data?

How does the analysis of the data translate into decisions?

Submit your answers in a 4- to 5-page Microsoft Word document.

Hands-On Analysis

Select one of the datasets included with your textbook (on a CD). Open the selected data file in Microsoft Excel software; choose three continuous and two discrete measures and perform the following:

For the continuous variables, compute all available measures of central tendency, range, and dispersion; display your results numerically and graphically. Describe the distribution of each variable. Which variable exhibits the greatest amount of variability? What is the basis of your conclusion?

For each of the two discrete variables, compute all applicable descriptive measures; show your results numerically and graphically. Compare and contrast the two variables in terms of the measures you computed.

Submit your answers in a 4- to 5-page Microsoft Word document

can you do both of these assignment by Thursday 22 I sent data set is a early reply for on hand anylysis

Can't help with the first one. Second one requires 4-5 page report, but the analysis might not satisfy that requirement. So, you may have to add something on your own. And while it may not reflect with the size of answers, these analysis take some considerable time. So, I hope you appreciated the work with bonuses.

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