Resource: Pastas R Us, Inc. Database Review the Wk 2 - Apply: Statistical Report assignment. In preparation for writing your report to senior management next week, conduct the following descriptive statistics analyses with Excel®. Answer the questions below in your Excel sheet or in a separate Word document:Insert a new column in the database that corresponds to “Annual Sales.” Annual Sales is the result of multiplying a restaurant’s “SqFt.” by “Sales/SqFt.”Calculate the mean, standard deviation, skew, 5-number summary, and interquartile range (IQR) for each of the variables.Create a box-plot for the “Annual Sales” variable. Does it look symmetric? Would you prefer the IQR instead of the standard deviation to describe this variable’s dispersion? Why?Create a histogram for the “Sales/SqFt” variable. Is the distribution symmetric? If not, what is the skew? Are there any outliers? If so, which one(s)? What is the “SqFt” area of the outlier(s)? Is the outlier(s) smaller or larger than the average restaurant in the database? What can you conclude from this observation?What measure of central tendency is more appropriate to describe “Sales/SqFt”? Why?Below I have listed the instructions for week 2. This portion is to only help complete the assignment listed above in bold.Resources: 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 oldHousehold median income above national averageAt least 15% college educated adult populationLast 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 statisticsSection 2: AnalysisSection 3: Recommendations and ImplementationSection 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?)PLEASE NO PLAGIARISM, LIST REFERENCES IF NEEDED. PLEASE LET ME KNOW IF YOU HAVE QUESTIONS

The formula for calculating a 95% confidence interval for a population mean is: The general “Confidence Interval” formula is: sample mean – E < population mean < sample mean + E To calculate a confidence interval, the margin of error (E) must first be calculated. The Margin of Error, E, for means is: E = 1.96*s/sqrt(n), where s is the sample standard deviation, n is the sample size. The “sqrt” stands for square root. The Margin of Error, E, for proportions is: E = 1.96*sqrt[p*(1-p)/n], where s is the sample standard deviation, n is the sample size, and p is the proportion. Use the Confidence Interval formula above, and the correct formula for E, to and calculate the 95% confidence interval for any population mean of your choice. Write down (invent) the sample size (be sure it is 30 or above), the sample mean, and the sample standard deviation. Then, calculate the confidence interval. Remember, you are inventing all the values, so no two posts should look the same. Use the Confidence Interval formula above, and the correct formula for E, to and calculate the 95% confidence interval for any population proportion of your choice. Write down (invent) the sample size (be sure it is 30 or above) and the sample proportion. Then, calculate the confidence interval. Remember, you are inventing all the values, so no two posts should look the same. Hint: The PowerPoint Guides has great examples to learn from before creating your own unique and original example. Please create personalized and substantive responses to at least two other student main posts. In your response, include the following: Choose any two classmates and review their main posts. Review all student work for calculating a confidence interval for a sample mean. Redo their work and confirm that it is correct, or correct it and note the errors. What is the final margin of error E? What is the final confidence interval? Offer an example sample mean that would fit into the confidence interval. Offer an example sample mean that would be outside of the confidence interval. Review all student work for calculating a confidence interval for a sample proportion. Redo their work and confirm that it is correct, or correct it and note the errors. What is the final margin of error E? What is the final confidence interval? Offer an example sample proportion that would fit into the confidence interval. Offer an example sample proportion that would be outside of the confidence interval.            TEXTBOOKS  Bennett, J., Briggs, W.L. & Triola, M.F. (2013) Statistical Reasoning for Everyday Life (4th ed.). Upper Saddle, NJ: Pearson.