Having studied and evaluated different challenges and opportunities associated with the use of secondary data, and having learned how to evaluate, analyze, and present information generated from the analysis of secondary data, now is your opportunity to synthesize this information and present your work.This week, you will compile all of the Assignments and your Instructor’s recommended changes into a Final Scholar-Practitioner Project Report.To prepare:Review the Ostchega, et al. (2012) article located in this week’s Learning Resources as an example for formatting your final report.Your Final Scholar-Practitioner Project Report should be 20 pages (excluding title page and references).Make sure to include the following in your report:Title pageResearch topic and backgroundResearch questionSecondary data set usedHow data collected in this data setValidity and reliability of the data setData analysis plan (variables and statistical procedures)Data dictionary and data tableResults and interpretation (descriptive and inferential tables)Descriptive analysis tables or graphs with interpretationInferential analysis tables or graphs with interpretationLimitations of studyTwo recommendations for future researchImplications for social changeReferencesSupport your paper with additional scholarly resources. Use APA formatting for your paper and to cite your resources.ReferencesOstchega, Y., Zhang, G., Sorlie, P., Hughes, J. P., Reed-Gillette, D. S., Nwankwo, T., & Yoon, S. (2012). Blood pressure randomized methodology study comparing automatic oscillometric and mercury sphygmomanometer devices: National Health and Nutrition Examination Survey, 2009–2010. National Health Statistics Reports, no 59. Retrieved from http://www.cdc.gov/nchs/data/nhsr/nhsr059.pdf

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 Click for more optionsthat 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 using the excel functions.

Goal Setting and GPACetin (2015) was interested in individual differences in goal setting behavior and performance in college students. To investigate the hypothesized association between the two variables, Cetin collected goal setting and grade point average (GPA) data from 166 college students. Goal setting was measured with a subscale from the Academic Self-Regulated Learning Scale. Students' GPA was measured via self-report. The goal_setting_gpa.csv data set simulates some of the data so that it corresponds to the results in the original study. We can use it to (a) the null hypothesis that there is no association between self-reported goal setting behavior and self-reported academic performance, and (b) construct a regression equation for predicting GPA from goal setting behavior.Cetin, B. (2015). Academic motivation and self-regulated learning in predicting academic achievement in college. Journal of International Education Research, 11(2), 95-106.(1) Download goal_setting_gpa.csv and open it in Jamovi.(2) Make sure the measure type and data type of the variables are correct.(3) From the Regression menu select Correlation Matrix. (4) In the Analysis panel, move gpa into the Variables box first and then goal_setting. We do it in this order because gpa is the variable we want to predict, which means that on a scatterplot, it should appear on the Y axis.(5) From the Correlation Coefficients menu select Pearson.(6) From the Hypothesis menu select Correlated.This specifies the alternative hypothesis, that the two varoables are correlated.(7) From the Additional Options menu select Report significance and N.(8) From the Plot menu select Correlation Matrix.(9) While still in the Analysis panel, from the Regression menu at the top, select Linear Regression.(10) Move gpa to the Dependent Variable box and move goal-setting to the Covariates box.(11) From the Model Fit menu select R, R2, and RMSE (which is the same thing as standard error of estimate).(12) Save the Jamovi file as Ch14_YourLastName.omv and use it to answer the questions on the worksheet.Instructions for submitting this assignment.(1) Locate Ch14_YourLastName.omv, and Ch14 Homework.docx where you saved them on your computer.(2) Click the title of this assignment (Ch14 Homework) to open the Upload Assignment page.(3) In the ASSIGNMENT SUBMISSION section, attach Ch14_YourLastName.omv and the Ch14 Homework file. Click Submit.(4) If you submit this assignment early enough, I might have time to provide feedback that you can use to improve it and possibly improve your grade. So soon after you submit it, return to this assignment to see if I've given you any feedback. Click the assignment title and on the Review Submission History page you'll see the details of your prior submissions. To revise a prior submission, click Start New, download and revise, be sure to save it, and upload it as previously.