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Sun Coast Remediation Data Set Discussion
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regress ...
Sun Coast Remediation Data Set Discussion
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations.
Correlation: Hypothesis Testing
Restate the hypotheses:
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1: There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses:
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses:
Ha3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, and the regression model as an equation with explanation.
12 pages
Queing Qns
According to the case study, The PATA clinic comprises of a pre-screened system to help in performing medical surgeries in ...
Queing Qns
According to the case study, The PATA clinic comprises of a pre-screened system to help in performing medical surgeries in their treatment operations. ...
11 pages
Chi Square Goodness Of Fit
Historically, the MBA program at Whatsamattu U. has about 40% of their students choose a Leadership major, 30% prefer Fina ...
Chi Square Goodness Of Fit
Historically, the MBA program at Whatsamattu U. has about 40% of their students choose a Leadership major, 30% prefer Finance major, 20% want ...
Deliverable 2 - Tutoring on the Normal Distribution
CompetencyDemonstrate the use of the normal distribution, the standard normal distribution, and the central limit theorem ...
Deliverable 2 - Tutoring on the Normal Distribution
CompetencyDemonstrate the use of the normal distribution, the standard normal distribution, and the central limit theorem for calculating areas under the normal curve and exploring these concepts in real life applications.ScenarioFrank has only had a brief introduction to statistics when he was in high school 12 years ago, and that did not cover inferential statistics. He is not confident in his ability to answer some of the problems posed in the course.As Frank's tutor, you need to provide Frank with guidance and instruction on a spreadsheet he has partially filled out. Your job is to help him understand and comprehend the material. You should not simply be providing him with an answer as this will not help when it comes time to take the test. Instead, you will be providing a step-by-step breakdown of the problems including an explanation on why you did each step and using proper terminology.What to SubmitTo complete this assignment, you must first download the spreadsheet, and then complete it by including the following items:1. Incorrect AnswersCorrect any wrong answers. You must also explain the error performed in the problem in your own words.2. Partially Finished WorkComplete any partially completed work. Make sure to provide step-by-step instructions including explanations.3. Blank ProblemsShow how to complete any blank questions by providing step-by-step instructions including explanations.Your step-by-step breakdown of the problems, including explanations and calculations performed should be present within the Excel workbook provided.
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Most Popular Content
Sun Coast Remediation Data Set Discussion
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regress ...
Sun Coast Remediation Data Set Discussion
Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations.
Correlation: Hypothesis Testing
Restate the hypotheses:
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1: There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses:
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses:
Ha3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, and the regression model as an equation with explanation.
12 pages
Queing Qns
According to the case study, The PATA clinic comprises of a pre-screened system to help in performing medical surgeries in ...
Queing Qns
According to the case study, The PATA clinic comprises of a pre-screened system to help in performing medical surgeries in their treatment operations. ...
11 pages
Chi Square Goodness Of Fit
Historically, the MBA program at Whatsamattu U. has about 40% of their students choose a Leadership major, 30% prefer Fina ...
Chi Square Goodness Of Fit
Historically, the MBA program at Whatsamattu U. has about 40% of their students choose a Leadership major, 30% prefer Finance major, 20% want ...
Deliverable 2 - Tutoring on the Normal Distribution
CompetencyDemonstrate the use of the normal distribution, the standard normal distribution, and the central limit theorem ...
Deliverable 2 - Tutoring on the Normal Distribution
CompetencyDemonstrate the use of the normal distribution, the standard normal distribution, and the central limit theorem for calculating areas under the normal curve and exploring these concepts in real life applications.ScenarioFrank has only had a brief introduction to statistics when he was in high school 12 years ago, and that did not cover inferential statistics. He is not confident in his ability to answer some of the problems posed in the course.As Frank's tutor, you need to provide Frank with guidance and instruction on a spreadsheet he has partially filled out. Your job is to help him understand and comprehend the material. You should not simply be providing him with an answer as this will not help when it comes time to take the test. Instead, you will be providing a step-by-step breakdown of the problems including an explanation on why you did each step and using proper terminology.What to SubmitTo complete this assignment, you must first download the spreadsheet, and then complete it by including the following items:1. Incorrect AnswersCorrect any wrong answers. You must also explain the error performed in the problem in your own words.2. Partially Finished WorkComplete any partially completed work. Make sure to provide step-by-step instructions including explanations.3. Blank ProblemsShow how to complete any blank questions by providing step-by-step instructions including explanations.Your step-by-step breakdown of the problems, including explanations and calculations performed should be present within the Excel workbook provided.
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