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If you have properly completed your SAS project you will upload the following th

If you have properly completed your SAS project you will upload the following three items:1. The DOCX file with the original assignment and rubric (all fields completed).2. The XLSX file you downloaded with the addition of the tab with the Scatterplots on it and the Regression Output tab for the regression of Price with the three independent variables.3. A PDF file you produce from SAS that shows the output of your final regression (with a higher R2 than we had with the original model).One critical thing to remember – you must correctly categorize your data types. Nominal data goes into the “Classification” variables when building your model, and all numeric data types going into “Continuous”.For the SAS (Critical Thinking) project, I always want to add clarity regarding the output from Excel Regression (see below). The Output gives you what you need to complete the Critical Thinking Project form for the Excel part. You will see below that I highlighted “R” (called Multiple R here and Correlation Coefficient in my slides) in Yellow. R2 is highlighted in Blue (that is the Coefficient of Determination). Remember, if you multiply it by 100, you get the percentage of the change in the Dependent Variable that is explained by the Independent Variable(s) – in this case 92.6%.Finally, you need to know how to build your Regression model from the output below. The formula coefficients are highlighted below in Green. This is the output from the Nodel Construction example you find in the PowerPoint slides for Chapter 4. If Sales is “Y,” Payroll is X1, and Interest Rate is X2, then your Regression model would read as follows:Y = 5.214 – 0.017(X1) – 30.155(X2)SUMMARY OUTPUTRegression StatisticsMultiple R0.96207063R Square0.925579897Adjusted R Square0.875966495Standard Error0.222740661Observations6ANOVA dfRegression2Residual3Total5 CoefficientsIntercept5.213917526Payroll-0.016752577Interest Rate-30.15463918
Requirements: 300

In the Independent Research Project (IRP), students conduct an analysis project

In the Independent Research Project (IRP), students conduct an analysis project using SAS primarily and Excel as needed to analyze real-world data. Note: You are required to do a ANOVA Analysis or a Regression Analysis and submit them showing Pr or P values, R-square, B values, Plots, etc. – as needed for the type of analysis you are conducting (ANOVA or Regression). Homogeneity of Variance of residuals can be assumed so you can proceed with your required analysis. Use DAX 4 or DAX 5 video and Instructions to help conduct your analysis.In this assignment, you will create and submit a business memo (template attached) that clearly communicates your analysis of the data set you identified in the previous assignment. When you submit this draft of your IRP, you will get feedback from your classmates and your instructor. You should use this feedback to improve your IRP.
Requirements: 5-10

Choose any well-known, publicly-traded company and write a 5 Forces analysis of

Choose any well-known, publicly-traded company and write a 5 Forces analysis of its industry. If you’re not familiar with this concept, check out the reference to Porter’s 5 Forces in the class lecture notes.
Find an example of a company that discontinued a product or service line. Why did it make this decision? From the time that the company added this product or service to the time that the company dropped it, what do you think changed?
How is a countplot in seaborn different from a barplot? Create an example of either type of plot, and write a few sentences that describe what it shows. (you may either upload an HTML file generated in Jupyter Notebook that includes your visualization and written statements, or a screenshot of your results along with your written statements — either way is fine).
Choose one of topic above, write200-250 words discussion post
Requirements: N/A

Enter your answers in the empty code chunks. Replace “# your code here” with you

Enter your answers in the empty code chunks. Replace “# your code here” with your code.Make sure you run this chunk before attempting any of the problems:library(tidyverse)2 BasicsCalculate 2+22+2:2+2## [1] 4Calculate 2∗32∗3:# your code hereCalculate (2+2)×(32+5)(6/4)(2+2)×(32+5)(6/4):# your code here3 dplyrLet’s work with the data set diamonds:data(diamonds) # this will load a dataset called “diamonds”Calculate the average price of a diamond. Use the %>% and summarise() syntax (hint: see lectures).# your code hereCalculate the average, median and standard deviation price of a diamond. Use the %>% and summarise() syntax.# your code hereUse group_by() to group diamonds by color, then use summarise() to calculate the average price and the standard deviation in price by color:# your code hereUse filter() to remove observations with a depth greater than 62, then usegroup_by() to group diamonds by clarity, then use summarise() to find the maximum price of a diamond by clarity:# your code hereUse mutate() and log() to create a new variable to the data called “log_price”. Make sure you add the variable to the dataset diamonds.# your code here(Hint: if I wanted to add a variable called “max_price” that calculates the max price, the code would look like this:)diamonds = diamonds %>%
mutate(max_price = max(price))4 ggplot2Continue using diamonds.Use geom_histogram() to plot a histogram of prices:# your code hereUse geom_density() to plot the density of log prices (the variable you added to the data frame):# your code hereUse geom_point() to plot carats against log prices (i.e. carats on the x-axis, log prices on the y-axis):# your code hereSame as above, but now add a regression line with geom_smooth():# your code hereUse stat_summary() to make a bar plot of average log price by cut:# your code hereSame as above but change the theme to theme_classic():# your code here5 InferenceUse lm() to estimate the modellog(price)=β0+β1carat+β2table+εlog(price)=β0+β1carat+β2table+εand store the output in an object called “m1”:# your code hereUse summary() to view the output of “m1”:# your code hereUse lm() to estimate the modellog(price)=β0+β1carat+β2table+β3depth+εlog(price)=β0+β1carat+β2table+β3depth+εand store the output in an object called “m2”:# your code hereUse summary() to view the output of “m2”:# your code here
Requirements: No required

At teradatauniversitynetwork.com, go to the Sports Analytics page. Find applicat

At teradatauniversitynetwork.com, go to the Sports Analytics page. Find applications of Big Data in sports. Summarize your findings.
What is Big Data? Why is it important? Where does Big Data come from?
What do you think the future of Big Data will be? Will it lose its popularity to something else? If so, what will it be?
What is Big Data analytics? How does it differ from regular analytics?
What are the critical success factors for Big Data analytics?
What are the big challenges that one should be mindful of when considering implementation of Big Data analytics?
Please include intext citations and references
Requirements: 2pages

Assignment ContentResources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1

Assignment ContentResources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1: Descriptive Statistics Analysis AssignmentPurpose This assignment is intended to help you learn how to apply statistical methods when analyzing operational data, evaluating the performance of current marketing strategies, and recommending actionable business decisions. This is an opportunity to build critical-thinking and problem-solving skills within the context of data analysis and interpretation. You’ll gain a first-hand understanding of how data analytics supports decision-making and adds value to an organization.
Scenario:
Pastas R Us, Inc. is a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. Since its inception, the business development team has favored opening new restaurants in areas (within a 3-mile radius) that satisfy the following demographic conditions:
Median age between 25 – 45 years old
Household median income above national average
At least 15% college educated adult population
Last year, the marketing department rolled out a Loyalty Card strategy to increase sales. Under this program, customers present their Loyalty Card when paying for their orders and receive some free food after making 10 purchases.
The company has collected data from its 74 restaurants to track important variables such as average sales per customer, year-on-year sales growth, sales per sq. ft., Loyalty Card usage as a percentage of sales, and others. A key metric of financial performance in the restaurant industry is annual sales per sq. ft. For example, if a 1200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.
Executive management wants to know whether the current expansion criteria can be improved. They want to evaluate the effectiveness of the Loyalty Card marketing strategy and identify feasible, actionable opportunities for improvement. As a member of the analytics department, you’ve been assigned the responsibility of conducting a thorough statistical analysis of the company’s available database to answer executive management’s questions.
Report:
Write a 750-word statistical report that includes the following sections:Section 1: Scope and descriptive statistics
Section 2: Analysis
Section 3: Recommendations and Implementation
Section 1 – Scope and descriptive statisticsState the report’s objective.
Discuss the nature of the current database. What variables were analyzed?
Summarize your descriptive statistics findings from Excel. Use a table and insert appropriate graphs.
Section 2 – Analysis Using Excel, create scatter plots and display the regression equations for the following pairs of variables:
“BachDeg%” versus “Sales/SqFt”
“MedIncome” versus “Sales/SqFt”
“MedAge” versus “Sales/SqFt”
“LoyaltyCard(%)” versus “SalesGrowth(%)”
In your report, include the scatter plots. For each scatter plot, designate the type of relationship observed (increasing/positive, decreasing/negative, or no relationship) and determine what you can conclude from these relationships.
Section 3: Recommendations and implementationBased on your findings above, assess which expansion criteria seem to be more effective.Could any expansion criterion be changed or eliminated? If so, which one and why?
Based on your findings above, does it appear as if the Loyalty Card is positively correlated with sales growth? Would you recommend changing this marketing strategy?
Based on your previous findings, recommend marketing positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)
Indicate what information should be collected to track and evaluate the effectiveness of your recommendations. How can this data be collected? (Hint: Would you use survey/samples or census?)
Cite references to support your assignment.
Format your citations according to APA guidelines.
Submit your assignment.
Requirements: 750   |   .doc file

Assignment ContentResources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1

Assignment ContentResources: Pastas R Us, Inc. Database & Microsoft Excel®, Wk 1: Descriptive Statistics Analysis AssignmentPurpose This assignment is intended to help you learn how to apply statistical methods when analyzing operational data, evaluating the performance of current marketing strategies, and recommending actionable business decisions. This is an opportunity to build critical-thinking and problem-solving skills within the context of data analysis and interpretation. You’ll gain a first-hand understanding of how data analytics supports decision-making and adds value to an organization.
Scenario:
Pastas R Us, Inc. is a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. Since its inception, the business development team has favored opening new restaurants in areas (within a 3-mile radius) that satisfy the following demographic conditions:
Median age between 25 – 45 years old
Household median income above national average
At least 15% college educated adult population
Last year, the marketing department rolled out a Loyalty Card strategy to increase sales. Under this program, customers present their Loyalty Card when paying for their orders and receive some free food after making 10 purchases.
The company has collected data from its 74 restaurants to track important variables such as average sales per customer, year-on-year sales growth, sales per sq. ft., Loyalty Card usage as a percentage of sales, and others. A key metric of financial performance in the restaurant industry is annual sales per sq. ft. For example, if a 1200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.
Executive management wants to know whether the current expansion criteria can be improved. They want to evaluate the effectiveness of the Loyalty Card marketing strategy and identify feasible, actionable opportunities for improvement. As a member of the analytics department, you’ve been assigned the responsibility of conducting a thorough statistical analysis of the company’s available database to answer executive management’s questions.
Report:
Write a 750-word statistical report that includes the following sections:Section 1: Scope and descriptive statistics
Section 2: Analysis
Section 3: Recommendations and Implementation
Section 1 – Scope and descriptive statisticsState the report’s objective.
Discuss the nature of the current database. What variables were analyzed?
Summarize your descriptive statistics findings from Excel. Use a table and insert appropriate graphs.
Section 2 – Analysis Using Excel, create scatter plots and display the regression equations for the following pairs of variables:
“BachDeg%” versus “Sales/SqFt”
“MedIncome” versus “Sales/SqFt”
“MedAge” versus “Sales/SqFt”
“LoyaltyCard(%)” versus “SalesGrowth(%)”
In your report, include the scatter plots. For each scatter plot, designate the type of relationship observed (increasing/positive, decreasing/negative, or no relationship) and determine what you can conclude from these relationships.
Section 3: Recommendations and implementationBased on your findings above, assess which expansion criteria seem to be more effective.Could any expansion criterion be changed or eliminated? If so, which one and why?
Based on your findings above, does it appear as if the Loyalty Card is positively correlated with sales growth? Would you recommend changing this marketing strategy?
Based on your previous findings, recommend marketing positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)
Indicate what information should be collected to track and evaluate the effectiveness of your recommendations. How can this data be collected? (Hint: Would you use survey/samples or census?)
Cite references to support your assignment.
Format your citations according to APA guidelines.
Submit your assignment.
Requirements: 750   |   .doc file

In the Independent Research Project (IRP), students conduct an analysis project

In the Independent Research Project (IRP), students conduct an analysis project using SAS primarily and Excel as needed to analyze real-world data. Note: You are required to do a ANOVA Analysis or a Regression Analysis and submit them showing Pr or P values, R-square, B values, Plots, etc. – as needed for the type of analysis you are conducting (ANOVA or Regression). Homogeneity of Variance of residuals can be assumed so you can proceed with your required analysis. Use DAX 4 or DAX 5 video and Instructions to help conduct your analysis.In this assignment, you will create and submit a business memo (template attached) that clearly communicates your analysis of the data set you identified in the previous assignment. When you submit this draft of your IRP, you will get feedback from your classmates and your instructor. You should use this feedback to improve your IRP.
Requirements: 8 Pages word file   |   .doc file

This assignment is intended to help you learn how to apply statistical methods w

This assignment is intended to help you learn how to apply statistical methods when analyzing operational data, evaluating the performance of current marketing strategies, and recommending actionable business decisions. This is an opportunity to build critical-thinking and problem-solving skills within the context of data analysis and interpretation. You’ll gain a first-hand understanding of how data analytics supports decision-making and adds value to an organization.Scenario: Pastas R Us, Inc. is a fast-casual restaurant chain specializing in noodle-based dishes, soups, and salads. Since its inception, the business development team has favored opening new restaurants in areas (within a 3-mile radius) that satisfy the following demographic conditions:Median age between 25 – 45 years old
Household median income above national average
At least 15% college educated adult population
Last year, the marketing department rolled out a Loyalty Card strategy to increase sales. Under this program, customers present their Loyalty Card when paying for their orders and receive some free food after making 10 purchases.The company has collected data from its 74 restaurants to track important variables such as average sales per customer, year-on-year sales growth, sales per sq. ft., Loyalty Card usage as a percentage of sales, and others. A key metric of financial performance in the restaurant industry is annual sales per sq. ft. For example, if a 1200 sq. ft. restaurant recorded $2 million in sales last year, then it sold $1,667 per sq. ft.Executive management wants to know whether the current expansion criteria can be improved. They want to evaluate the effectiveness of the Loyalty Card marketing strategy and identify feasible, actionable opportunities for improvement. As a member of the analytics department, you’ve been assigned the responsibility of conducting a thorough statistical analysis of the company’s available database to answer executive management’s questions.Report: Write a 750-word statistical report that includes the following sections:Section 1: Scope and descriptive statistics
Section 2: Analysis
Section 3: Recommendations and Implementation
Section 1 – Scope and descriptive statisticsState the report’s objective.
Discuss the nature of the current database. What variables were analyzed?
Summarize your descriptive statistics findings from Excel. Use a table and insert appropriate graphs.
Section 2 – Analysis Using Excel, create scatter plots and display the regression equations for the following pairs of variables:
“BachDeg%” versus “Sales/SqFt”
“MedIncome” versus “Sales/SqFt”
“MedAge” versus “Sales/SqFt”
“LoyaltyCard(%)” versus “SalesGrowth(%)”
In your report, include the scatter plots. For each scatter plot, designate the type of relationship observed (increasing/positive, decreasing/negative, or no relationship) and determine what you can conclude from these relationships.
Section 3: Recommendations and implementationBased on your findings above, assess which expansion criteria seem to be more effective.Could any expansion criterion be changed or eliminated? If so, which one and why?
Based on your findings above, does it appear as if the Loyalty Card is positively correlated with sales growth? Would you recommend changing this marketing strategy?
Based on your previous findings, recommend marketing positioning that targets a specific demographic. (Hint: Are younger people patronizing the restaurants more than older people?)
Indicate what information should be collected to track and evaluate the effectiveness of your recommendations. How can this data be collected? (Hint: Would you use survey/samples or census?)
Cite references to support your assignment.Format your citations according to APA guidelines.
Requirements: 750 Words

Respond to the following in a minimum of 175 words:The most frequently used meas

Respond to the following in a minimum of 175 words:The most frequently used measures of central tendency for quantitative data are the mean and the median. The following table shows civil service examination scores from 24 applicants to law enforcement jobs:83 74 85 7982 67 78 7018 93 64 2793 98 82 7868 82 83 9996 62 93 58Using Excel, find the mean, standard deviation, and 5-number summary of this sample.Construct and paste a box plot depicting the 5-number summary.
Does the dataset have outliers? If so, which one(s)?
Would you prefer to use the mean or the median as this dataset’s measure of central tendency? Why?
Requirements: 175 words