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If x and y are distinct, positive, real numbers, then (x/y) + (y/x)>2
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PUBH8545 Medical Exploration Screening for Cardiovascular Disease Report
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PUBH8545 Medical Exploration Screening for Cardiovascular Disease Report
In many different situations, you may be exposed to information that requires further analysis; this may be true as you receive reports, read a journal, or prepare for a presentation. What is certain is that you should always approach results in a critical but unbiased way, and be prepared to address any potential weaknesses in the reported data.For this Discussion, you will evaluate recommendations made based on the results of a study from a given scenario.To prepare:Select one of the following scenarios:Scenario 1: A sample of 5,000 swimmers and 5,000 runners were screened for cardiovascular disease (CVD). The study found that the rate of CVD is 33.3% in swimmers and 30.9% in runners, with the p-value of <0.05. A public campaign is recommended to promote running instead of swimming activities.Scenario 2: A study of 1,000 married women was conducted concerning pre-marital birth and the success of the subsequent marriages. The study reported that less educated women were 30% more likely to have children before marriage than highly educated women. In addition, 40% of the African-American women in the study had children before marriage. The study concluded that marriage counseling should be provided to less educated women and to African-American women.Post an evaluation of the recommendation from your scenario. Include the following in your post:The scenario number you selectedYour evaluation of whether the recommendations are overstated or understated based on the results described in the scenario (justify your response)Your suggestion of two methods for addressing and correcting those errorsSupport your post with the Learning Resources and current literature. Use APA formatting for your Discussion and to cite your resources.Referenceshttps://class.waldenu.edu/bbcswebdav/institution/USW1/201950_27/PH_PUBH/PUBH_8545_WC/readings/USW1_PUBH_8545_Week10_wantedValidAndMeaningfulData.pdfFullerton, S. M., & Lee, S. S. (2011). Secondary uses and the governance of de-identified data: Lessons from the human genome diversity panel. BMC Medical Ethics, 12(1), 16.
American College of Education Advanced Topics in Statistics Questions
i need fixt it For question 2a, check the “id” variable to be sure you have the correct cases numbers that need to be ...
American College of Education Advanced Topics in Statistics Questions
i need fixt it For question 2a, check the “id” variable to be sure you have the correct cases numbers that need to be removed. There are three cases that should be removed that you did not list. Also, 18 and 1129 will automatically be removed since there is missing data for these cases (no MAH_1 value). Some of your values are different than what I have. Be sure you run the multiple regression with the profile-b data set and only with cases that are MAH_1 ≤ 22.458. For question 2h, you should not include the values for the variables that are not statistically significant. The regression equation should only include those variables that are statistically significant. For 2i, also mention that these two variables are not statistically significant and provide the p (sig) value.
Discussion Questions
1. Review the four "ANOVA" videos in the Calculations section of the "Statistics Visual Learner" media piece.Explain the m ...
Discussion Questions
1. Review the four "ANOVA" videos in the Calculations section of the "Statistics Visual Learner" media piece.Explain the major differences between analyzing a one-way ANOVA versus a two-factor ANOVA, and explain why factorial designs with two or more independent variables (or factors) can become very difficult to interpret.2. Explain how the ANOVA technique avoids the problem of the inflated probability of making Type I error that would arise using the alternative method of comparing groups two at a time using the t-test for independent groups.
Murray State University Hypothesis Testing Procedures Statistics Quiz
I uploaded the questions for the statistics quiz. see attachment below. only material i have is the book for the class. th ...
Murray State University Hypothesis Testing Procedures Statistics Quiz
I uploaded the questions for the statistics quiz. see attachment below. only material i have is the book for the class. the questions cover chapters 15 and 16 of "Statistical Reasoning in the Behavioral Sciences SEVENTH EDITION Bruce M. King Patrick J. Rosopa Edward W. Minium" https://drive.google.com/open?id=1JxDIjEv7hCkUaeNn...I want 95% or more for sure.
Deliverable 6 - Analysis with Correlation and Regression
CompetencyDetermine the linear correlation and regression equation between two variables to make predictions for the depen ...
Deliverable 6 - Analysis with Correlation and Regression
CompetencyDetermine the linear correlation and regression equation between two variables to make predictions for the dependent variable.Student Success CriteriaView the grading rubric for this deliverable by selecting the “This item is graded with a rubric” link, which is located in the Details & Information pane.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 kmWhat to SubmitThe 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.
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Most Popular Content
PUBH8545 Medical Exploration Screening for Cardiovascular Disease Report
In many different situations, you may be exposed to information that requires further analysis; this may be true as you re ...
PUBH8545 Medical Exploration Screening for Cardiovascular Disease Report
In many different situations, you may be exposed to information that requires further analysis; this may be true as you receive reports, read a journal, or prepare for a presentation. What is certain is that you should always approach results in a critical but unbiased way, and be prepared to address any potential weaknesses in the reported data.For this Discussion, you will evaluate recommendations made based on the results of a study from a given scenario.To prepare:Select one of the following scenarios:Scenario 1: A sample of 5,000 swimmers and 5,000 runners were screened for cardiovascular disease (CVD). The study found that the rate of CVD is 33.3% in swimmers and 30.9% in runners, with the p-value of <0.05. A public campaign is recommended to promote running instead of swimming activities.Scenario 2: A study of 1,000 married women was conducted concerning pre-marital birth and the success of the subsequent marriages. The study reported that less educated women were 30% more likely to have children before marriage than highly educated women. In addition, 40% of the African-American women in the study had children before marriage. The study concluded that marriage counseling should be provided to less educated women and to African-American women.Post an evaluation of the recommendation from your scenario. Include the following in your post:The scenario number you selectedYour evaluation of whether the recommendations are overstated or understated based on the results described in the scenario (justify your response)Your suggestion of two methods for addressing and correcting those errorsSupport your post with the Learning Resources and current literature. Use APA formatting for your Discussion and to cite your resources.Referenceshttps://class.waldenu.edu/bbcswebdav/institution/USW1/201950_27/PH_PUBH/PUBH_8545_WC/readings/USW1_PUBH_8545_Week10_wantedValidAndMeaningfulData.pdfFullerton, S. M., & Lee, S. S. (2011). Secondary uses and the governance of de-identified data: Lessons from the human genome diversity panel. BMC Medical Ethics, 12(1), 16.
American College of Education Advanced Topics in Statistics Questions
i need fixt it For question 2a, check the “id” variable to be sure you have the correct cases numbers that need to be ...
American College of Education Advanced Topics in Statistics Questions
i need fixt it For question 2a, check the “id” variable to be sure you have the correct cases numbers that need to be removed. There are three cases that should be removed that you did not list. Also, 18 and 1129 will automatically be removed since there is missing data for these cases (no MAH_1 value). Some of your values are different than what I have. Be sure you run the multiple regression with the profile-b data set and only with cases that are MAH_1 ≤ 22.458. For question 2h, you should not include the values for the variables that are not statistically significant. The regression equation should only include those variables that are statistically significant. For 2i, also mention that these two variables are not statistically significant and provide the p (sig) value.
Discussion Questions
1. Review the four "ANOVA" videos in the Calculations section of the "Statistics Visual Learner" media piece.Explain the m ...
Discussion Questions
1. Review the four "ANOVA" videos in the Calculations section of the "Statistics Visual Learner" media piece.Explain the major differences between analyzing a one-way ANOVA versus a two-factor ANOVA, and explain why factorial designs with two or more independent variables (or factors) can become very difficult to interpret.2. Explain how the ANOVA technique avoids the problem of the inflated probability of making Type I error that would arise using the alternative method of comparing groups two at a time using the t-test for independent groups.
Murray State University Hypothesis Testing Procedures Statistics Quiz
I uploaded the questions for the statistics quiz. see attachment below. only material i have is the book for the class. th ...
Murray State University Hypothesis Testing Procedures Statistics Quiz
I uploaded the questions for the statistics quiz. see attachment below. only material i have is the book for the class. the questions cover chapters 15 and 16 of "Statistical Reasoning in the Behavioral Sciences SEVENTH EDITION Bruce M. King Patrick J. Rosopa Edward W. Minium" https://drive.google.com/open?id=1JxDIjEv7hCkUaeNn...I want 95% or more for sure.
Deliverable 6 - Analysis with Correlation and Regression
CompetencyDetermine the linear correlation and regression equation between two variables to make predictions for the depen ...
Deliverable 6 - Analysis with Correlation and Regression
CompetencyDetermine the linear correlation and regression equation between two variables to make predictions for the dependent variable.Student Success CriteriaView the grading rubric for this deliverable by selecting the “This item is graded with a rubric” link, which is located in the Details & Information pane.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 kmWhat to SubmitThe 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.
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