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.ScenarioAccording 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.Concepts Being StudiedCorrelation and regressionCreating scatterplotsConstructing and interpreting a Hypothesis Test for Correlation using r as the test statisticYou are given a spreadsheet that contains the following information:Magnitude measured on the Richter scaleDepth in kmUsing the spreadsheet, you will answer the problems below in a PowerPoint presentation.What to SubmitThe PowerPoint presentation should answer and explain the following questions based on the spreadsheet provided above.Slide 1: Title slideSlide 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.

A company is looking at the results of a marketing survey and trying to establish whether men and women value the product differently. They have data on the willingness to pay for the product for 50 men and 50 women.Design a hypothesis test of whether or not the mean willingness to pay for the product is different for men and women.Which, if any, is more important to minimize in this case, the type I or type II error? Why?How does the choice of the critical value affect the tradeoff between the type I and type II error? 1-2 pages with two references. it is a discussion question