BUSN311_U3_IP

Please read the case and answer the following questions. CompStat (short for COMPuter STATistics or COMParative STATistics) originated in the New York City Police Department (NYPD) in 1994 when William Bratton was police commissioner. CompStat is a comprehensive, city-wide database that records all reported crimes or complaints, arrests, and summonses issued in each of the city’s 76 precincts. City officials had previously believed that crime could not be prevented by better information and analytical tools but instead by using more foot patrols in neighborhoods along with the concept of “community policing” in which efforts were made to strengthen the involvement of community groups. In contrast, Bratton and Rudy Giuliani, then the mayor of New York City, believed that. police could be more effective in reducing crime if operational decisions took place at the precinct level and if decision makers had better information. Precinct commanders were in a better position than police…

Please help me with thirdly part 1,2, and 3

The multiple linear regression analysis is one of the most reliable and accurate tools for cost estimating. The validity of the analysis depends on the relevance of the independent variables selected. Please respond to the following: Discuss what independent variables should be selected to estimate the maintenance costs for a manufacturing company using multiple linear regression analysis. Explain why these independent variables were selected. What are other variables should be considered, but decided not to include? Explain why.

Descibe and analyze how the Trend Approach in data analysis is the monitoring of variables to see how they change over time and how they can be used to predict future variable values. Discuss trend analysis in depth and the reasons companies rely on such strategy in their business operations. Discuss how Trend Analytics may encourage awareness and help a brand to grow. What are three examples of Trend Analysis that can be offered, that may help an organization gain a competitive edge in the industry in which it operates? Please utilize relevant Digital Marketing Analytics in the response.

Explain the meaning of business analytics and its role in generating value from data. Distinguish between model and modelling, and explain the steps in solving business problems using analytics.

what do the standardized regression weights or coefficients tell you about the ability of the predictors to predict the dependent variable?

Please use google looker studio

Paraphrase this one. Analyze and elaborate in 85 words. Regression analysis data also helps you understand whether the relationship between two different variables can give way to potential business opportunities.

Cost Estimation; High-Low and Regression Methods The Mac Davis Company specializesin the purchase, renovation, and resale of older homes. Mac employs several carpenters and paintersto do the work for him. It is essential for him to have accurate cost estimates so he can determinetotal renovation costs before he purchases a piece of property. If estimated renovation costs plus thepurchase price of a house are higher than the house’s estimated resale value, it is not a worthwhileinvestment.Mac has been using the home’s interior square feet for his exterior paint cost estimations. Recentlyhe decided to include the number of external openings—the total number of doors and windows ina house—as a cost driver. Their cost is significant because they require time-consuming preparatorywork and careful brushwork. The rest of the house usually is painted either by rollers or spray guns,which are relatively efficient ways to apply paint to a large area. Mac has kept careful records of theseexterior…

Collect sufficient data about any two quantitative variables (logically correlated) using reasonable sets of values (At least 15 values). Use Microsoft Excel and answer the following: Firstly: Determine the independent variable and the dependent variable. Secondly: Make the correlation analysis for the quantitative variables and determine the correlation coefficient, and interpret it. Thirdly: Do the regression analysis and answer the following questions: 1. What is the type of regression in your example? 2. Find the sample size. 3. Find the degrees of freedom. 4. Is your model valid? Why? 5. Find the value of the coefficient of determination, and interpret it. 6. Is the independent variable having a significant effect on the dependent variable? Why? 7. Write down the regression line equation. 8. Estimate the value of ŷ if the value of X is 20.

What is the difference between a simple regression equation and a multiple regression equation?

The table below summarizes September 20223 financial performance by two market segments. The dates highlighted in orange indicate occupancy higher than 90% Please find the correct statement about the data analysis based on the table. Market segment 1 shows pattern of peak on Weekdays. Market segment 2 shows a pattern of peak on Weekends. Based on the demand pattern, Market Segment 2 could be leisure travelers. Most guests in the market segment 2 are less price sensitive than those in the market segment 1.

what is the standardized regression? what do the standardized regression weights or coefficients tell us about the ability of the predictors to predict the dependent variable?

Create a line graph for this set of monthly sales numbers. Run a regression analysis.       What is the regression equation?     Is the regression equation significant? How can you tell? What is the Rsquare?  What does this signify?   What is the sales forecast for month 13?       1 550   2 548   3 546   4 549   5 550   6 548   7 551   8 551   9 552   10 551   11 553   12 553

please help me understand the problem

r In Excel Answer each of the following problem (II) using regression analysis (easiest way is using the scatter diagram approach. But you can also use the regression analysis routine in the Data Analysis module in Excel A sales manager collected the following data on annual sales and years of experience. a. b. C. Salesperson 1234567890 Years of Experience 1 3 4 4 6 8 : 10 10 11 13 Annual Sales ($1000s) 80 97 92 102 103 119 123 117 136 03 Develop a scatter diagram for these data with years of experience as the independent variable. Develop an estimated regression equation that can be used to predict annual given the years of experience. Use the estimated regression equation to predict annual sales for a salesperson 9 years of experience.

practical example of the USES of Statistics, in business applications.

. Suppose that you are working as an analyst. Your task is to value company XYZ based on financial data available for this company. Discuss how you would go about doing this using themultiple growth rate Gordon growth model. Critically evaluate your approach by discussing any assumptions you make (about forecasts, discount rate etc.). What data is needed to value XYZ?

A business conducted a linear regression to estimate its demand function and obtain the following demand function Q = 200 - 1.5P + 0.55A - 2.8Py + 0.05Inc, where P is price and A is advertising. When P = $21. A = $30 and Quantity = 160, find the profit-maximizing advertising-to-sales ratio (hint: first find the price and advertising elasticities). Type as either a decimal out two spaces, like 0.10 OR as a percentage like 10%. %3! %3! Question 17 During recessions, people's reservation price (aka reserve price) searching. which results in O drops; less O rises; more drops; more O rises; less

Please help with correct answers: step by step: last time submitted- answers were incorrect A statistical program is recommended. The quarterly sales data (number of copies sold) for a college textbook over the past three years follow. Quarter Year 1 Year 2 Year 3 1 1,690 1,800 1,850 2 940 900 1,100 3 2,625 2,900 2,930 4 2,500 2,360 2,615 a) Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. (Round your numerical values to the nearest integer.) Qrt1 = 1 if quarter 1, 0 otherwise; Qrt2 = 1 if quarter 2, 0 otherwise; Qrt3 = 1 if quarter 3, 0 otherwise t =    b) Using the equation developed in part (b), compute the quarterly forecasts for year 4. (Round your answers to the nearest ten.) quarter 1 forecast____? quarter 2 forecast____? quarter 3 forecast ____? quarter 4 forecast ____?   c) Let t = 1 refer to the observation in Quarter 1 of Year 1; let  t = 2 refer to the observation in Quarter 2 of Year…

What is differ from SMA (Simple moving average), WMA (Weighted moving average), SLR (Single linear regression), and ESM ( Exponential smoothing model).

This type of analysis is most appropriate when the past is a good predictor of the future.