Determine and interpret the linear correlation coefficient, and use linear regression to find a best fit line for a scatter plot of the data and make predictions. Scenario: According to the U.S. Geological Survey (USGS), the probability of a magnitude 6.7 or greater earthquake in the Greater Bay Area is 63%, about 2 out of 3, in the next 30 years. In April 2008, scientists and engineers released a new earthquake forecast for the State of California called the Uniform California Earthquake Rupture Forecast (UCERF). As a junior analyst at the USGS, you are tasked to determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and depths from the earthquakes. Your deliverables will be a PowerPoint presentation you will create summarizing your findings and an excel document to show your work. Concept being Studied Correlation and regression Creating scatterplots Constructing and interpreting a Hypothesis Test for Correlation using r as the test statistic You are given a spreadsheet that contains the following information: Magnitude measured on the Richter scale Depth in km Using the spreadsheet, you will answer the problems below in a PowerPoint presentation. What to Submit: The PowerPoint presentation should answer and explain the following questions based on the spreadsheet provided above. Slide 1: Title slide Slide 2: Introduce your scenario and data set including the variables provided. Slide 3: Construct a scatterplot of the two variables provided in the spreadsheet. Include a description of what you see in the scatterplot. Slide 4: Find the value of the linear correlation coefficient r and the critical value of r using α = 0.05. Include an explanation on how you found those values. Slide 5: Determine whether there is sufficient evidence to support the claim of a linear correlation between the magnitudes and the depths from the earthquakes. Explain. Slide 6: Find the regression equation. Let the predictor (x) variable be the magnitude. Identify the slope and the y-intercept within your regression equation. Slide 7: Is the equation a good model? Explain. What would be the best predicted depth of an earthquake with a magnitude of 2.0? Include the correct units. Slide 8: Conclude by recapping your ideas by summarizing the information presented in context of the scenario. Along with your PowerPoint presentation, you should include your Excel document which shows all calculations.

I need a walk through of how to complete the following in order to understand what actions to take and how to use Palisades @Risk in order to complete the problems. Using specified data files, chapter example files, and templates from the “Topic 2 Student Data, Template, and Example Files” topic material, complete Chapter 15, Problems 32 (parts a and b only), 33, and 35 from the textbook. Use the Palisade DecisionTools Excel software to complete these problems where requested and applicable. Use the Palisade DecisionTools Excel software to complete the rest of the problems and ensure that all Palisade software output is included in your files. Unless otherwise stated, run simulations with 1,000 trials. Use 500 trials if the software will not allow you to run 1,000 trials. Ensure that only one Excel file is open when running a simulation.32. A hardware company sells a lot of low-cost, high volume products. For one such product, it is equally likely that annual unit sales will be low or high. If sales are low (60,000), the company can sell the product for $10 per unit. If sales are high (100,000), a competitor will enter and the company will be able to sell the product for only $8 per unit. The variable cost per unit has a 25% chance of being $6, a 50% chance of being $7.50, and a 25% chance of being $9. Annual fixed costs are $30,000. a. Use simulation to estimate the company’s expected annual profit.b. Find a 95% interval for the company’s annual profit, that is, an interval such that about 95% of the actual profits are inside it.33. W. L. Brown, a direct marketer of women’s clothing, must determine how many telephone operators to schedule during each part of the day. W. L. Brown estimates that the number of phone calls received each hour of a typical eight-hour shift can be described by the probability distribution in the file P15_33.xlsx. Each operator can handle 15 calls per hour and costs the company $20 per hour. Each phone call that is not handled is assumed to cost the company $6 in lost profit. Considering the options of employing 6, 8, 10, 12, 14, or 16 operators, use simulation to determine the number of operators that minimizes the expected hourly cost (labor costs plus lost profits).35.Lemington’s is trying to determine how many Jean Hudson dresses to order for the spring season. Demand for the dresses is assumed to follow a normal distribution with mean 400 and standard deviation 100. The contract between Jean Hudson and Lemington’s works as follows. At the beginning of the season, Lemington’s reserves x units of capacity. xxLemington’s must take delivery for at least 0.8xdresses and can, if desired, take delivery on up to xdresses. Each dress sells for $160 and Hudson charges $50 per dress. If Lemington’s does not take delivery on all x dresses, it owes Hudson a $5 penalty for each unit of reserved capacity that is unused. For example, if Lemington’s orders 450 dresses and demand is for 400 dresses, Lemington’s will receive 400 dresses and owe Jean 400($50)+50($5). How many units of capacity should Lemington’s reserve to maximize its expected profit?To receive full credit on the assignment, complete the following.Ensure that the Palisade software output is included with your submission.Ensure that Excel files include the associated cell functions and/or formulas if functions and/or formulas are used.Include a written response to all narrative questions presented in the problem by placing it in the associated Excel file.Include screenshots of all simulation distribution results for output variables.