HCM-506-24410-202020 - (Current Semester - الفصل الحالي)HCM-506: Applied Biostatistics in Healt 24410-Riyadh-Males
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MASAUD ALYAMI
on Fri, Feb 26 2021, 7:42 PM
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Submission ID: 6802f609-2f75-4432-bb82-345a7758ad6a
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MULTIVARIATE ANALYSIS 1
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MULTIVARIATE ANALYSIS 1
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MULTIVARIATE ANALYSIS 1
MULTIVARIATE ANALYSIS 7
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MULTIVARIATE ANALYSIS 7
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MULTIVARIATE ANALYSIS 7
2
Applied Biostatistics in Health
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Applied Biostatistics in Health
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Applied Biostatistics in Health
Multivariate Analysis of Body Mass Index HCM-506 Masaud Alyami S199632635 February, 2021
Introduction
1
Body Mass Index (BMI) is an attribute calculated through the aspects of mass and height of a person.
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Body Mass Index (BMI) is an attribute calculated through the aspects of mass and height of a person
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Body Mass Index (BMI) is an attribute calculated through the aspects of mass and height of a person
The body mass is usually divided by the body height square, and its unit is expressed in kg/m2.
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The body mass is usually divided by the body height square, and its unit is expressed in kg/m2
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The body mass is usually divided by the body height square, and its unit is expressed in kg/m2
BMI values of below 20 and above 25 are attributed to high cases of mortality.
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BMI values of below 20 and above 25 are attributed to high cases of mortality
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BMI values of below 20 and above 25 are attributed to high cases of mortality
Thereby, the optimal range of Body Mass Index ranges from 20-25.
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Thereby, the optimal range of Body Mass Index ranges from 20-25
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Thereby, the optimal range of Body Mass Index ranges from 20-25
The tissue mass is a factor that is used to determine the overweight and underweight of a person.
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The tissue mass is a factor that is used to determine the overweight and underweight of a person
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The tissue mass is a factor that is used to determine the overweight and underweight of a person
There are a variety of factors that are used to determine the bodyweight of individuals.
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There are a variety of factors that are used to determine the bodyweight of individuals
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There are a variety of factors that are used to determine the bodyweight of individuals
These factors include age, diabetes, sex, and ethnicity (Emel Önal, 2019).
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These factors include age, diabetes, sex, and ethnicity (Emel Önal, 2019)
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These factors include age, diabetes, sex, and ethnicity (Emel Önal, 2019)
However, in this paper, we are going to use the Framingham Heart Study dataset to perform an ANOVA multivariable regression analysis with the use of BMI as a continuous variable.
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However, in this paper, we are going to use the Framingham Heart Study dataset to perform an ANOVA multivariable regression analysis with the use of BMI as a continuous variable
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However, in this paper, we are going to use the Framingham Heart Study dataset to perform an ANOVA multivariable regression analysis with the use of BMI as a continuous variable
The results that will be obtained will determine the factors that affect BMI in an individual.
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The results that will be obtained will determine the factors that affect BMI in an individual
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The results that will be obtained will determine the factors that affect BMI in an individual
The null and alternate hypothesis of the study is described below.
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The null and alternate hypothesis of the study is described below
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The null and alternate hypothesis of the study is described below
· H0 the BMI is not related to the patient characteristics in the Framingham Heart Study.
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· H0 the BMI is not related to the patient characteristics in the Framingham Heart Study
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· H0 the BMI is not related to the patient characteristics in the Framingham Heart Study
(Null Hypothesis) · H1 the BMI is related to the patient characteristics in the Framingham Heart Study.
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(Null Hypothesis) · H1 the BMI is related to the patient characteristics in the Framingham Heart Study
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(Null Hypothesis) · H1 the BMI is related to the patient characteristics in the Framingham Heart Study
(Alternative Hypothesis) Findings of the Study After analyzing how different concepts relate to Body Mass Index using multivariate regression, the following results were obtained:
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(Alternative Hypothesis) Findings of the Study After analyzing how different concepts relate to Body Mass Index using multivariate regression, the following results were obtained
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(Alternative Hypothesis) Findings of the Study After analyzing how different concepts relate to Body Mass Index using multivariate regression, the following results were obtained
Regression Statistics
1
Multiple R 0.05810995
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Multiple R 0.05810995
Source - Another student's paper
Multiple R 0.05810995
R Square 0.00337677
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
R Square 0.00337677
Source - Another student's paper
R Square 0.00337677
Adjusted R Square 0.00327301
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Adjusted R Square 0.00327301
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Adjusted R Square 0.00327301
Standard Error 4.0303178
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Standard Error 4.0303178
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Standard Error 4.0303178
Observations 9607
ANOVA
1
Df SS MS F Significance F
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Df SS MS F Significance F
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df SS MS F Significance F
Regression 1 528.62284 528.62284 32.5437307 1.1999E-08
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Regression 1 528.62284 528.62284 32.5437307 1.1999E-08
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Regression 1 528.62284 528.62284 32.5437307 1.1999E-08
Residual 9605 156018.449 16.2434616
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Residual 9605 156018.449 16.2434616
Source - Another student's paper
Residual 9605 156018.449 16.2434616
Total 9606 156547.071
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Total 9606 156547.071
Source - Another student's paper
Total 9606 156547.071
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
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Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
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Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 24.490722 0.23904879 102.450726 0 24.022136 24.9593081 24.022136 24.9593081
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Intercept 24.490722 0.23904879 102.450726 0 24.022136 24.9593081 24.022136 24.9593081
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Intercept 24.490722 0.23904879 102.450726 0 24.022136 24.9593081 24.022136 24.9593081
AGE 0.02472912 0.00433486 5.70471128 1.1999E-08 0.01623188 0.03322636 0.01623188 0.03322636
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AGE 0.02472912 0.00433486 5.70471128 1.1999E-08 0.01623188 0.03322636 0.01623188 0.03322636
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AGE 0.02472912 0.00433486 5.70471128 1.1999E-08 0.01623188 0.03322636 0.01623188 0.03322636
The p-value of the analysis between Body Mass Index and age is 1.1999E-08.
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The p-value of the analysis between Body Mass Index and age is 1.1999E-08
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The p-value of the analysis between Body Mass Index and age is 1.1999E-08
The p-value is less than 0.05, thereby the null hypothesis is rejected, and the alternate hypothesis is accepted.
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The p-value is less than 0.05, thereby the null hypothesis is rejected, and the alternate hypothesis is accepted
Source - Another student's paper
The p-value is less than 0.05, thereby the null hypothesis is rejected, and the alternate hypothesis is accepted
From this analysis, the BMI is related to the age of patients in the Framingham Heart Study dataset.
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From this analysis, the BMI is related to the age of patients in the Framingham Heart Study dataset
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From this analysis, the BMI is related to the age of patients in the Framingham Heart Study dataset
Older people tend to have an increased BMI in comparison to younger individuals.
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Older people tend to have an increased BMI in comparison to younger individuals
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Older people tend to have an increased BMI in comparison to younger individuals
At old age, people tend to be less active, making them increase their body muscles.
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At old age, people tend to be less active, making them increase their body muscles
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At old age, people tend to be less active, making them increase their body muscles
Regression Statistics
1
Multiple R 0.26630323
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Multiple R 0.26630323
Source - Another student's paper
Multiple R 0.26630323
R Square 0.07091741
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
R Square 0.07091741
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R Square 0.07091741
Adjusted R Square 0.07082068
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Adjusted R Square 0.07082068
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Adjusted R Square 0.07082068
Standard Error 3.89135587
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Standard Error 3.89135587
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Standard Error 3.89135587
Observations 9607
ANOVA
1
Df SS MS F Significance F
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Df SS MS F Significance F
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df SS MS F Significance F
Regression 1 11101.9133 11101.9133 733.155219 1.163E-155
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Regression 1 11101.9133 11101.9133 733.155219 1.163E-155
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Regression 1 11101.9133 11101.9133 733.155219 1.163E-155
Residual 9605 145445.158 15.1426505
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Residual 9605 145445.158 15.1426505
Source - Another student's paper
Residual 9605 145445.158 15.1426505
Total 9606 156547.071
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Total 9606 156547.071
Source - Another student's paper
Total 9606 156547.071
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
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Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Source - Another student's paper
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 19.3693733 0.24203325 80.0277387 0 18.8949371 19.8438095 18.8949371 19.8438095
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Intercept 19.3693733 0.24203325 80.0277387 0 18.8949371 19.8438095 18.8949371 19.8438095
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Intercept 19.3693733 0.24203325 80.0277387 0 18.8949371 19.8438095 18.8949371 19.8438095
SYSBP 0.04761088 0.00175836 27.0768392 1.163E-155 0.04416412 0.05105764 0.04416412 0.05105764
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SYSBP 0.04761088 0.00175836 27.0768392 1.163E-155 0.04416412 0.05105764 0.04416412 0.05105764
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SYSBP 0.04761088 0.00175836 27.0768392 1.163E-155 0.04416412 0.05105764 0.04416412 0.05105764
In the second regression analysis, BMI is compared to systolic blood pressure, and the p-value is ascertained to be 1.163E-155, which is below 0.05.
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In the second regression analysis, BMI is compared to systolic blood pressure, and the p-value is ascertained to be 1.163E-155, which is below 0.05
Source - Another student's paper
In the second regression analysis, BMI is compared to systolic blood pressure, and the p-value is ascertained to be 1.163E-155, which is below 0.05
Thus, the null hypothesis is rejected, and the alternate hypothesis is accepted.
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Thus, the null hypothesis is rejected, and the alternate hypothesis is accepted
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Thus, the null hypothesis is rejected, and the alternate hypothesis is accepted
Systolic blood pressure is related to BMI according to the provided dataset.
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Systolic blood pressure is related to BMI according to the provided dataset
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Systolic blood pressure is related to BMI according to the provided dataset
An increase in Body Mass Index also has a positive impact on the systolic blood pressure.
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An increase in Body Mass Index also has a positive impact on the systolic blood pressure
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An increase in Body Mass Index also has a positive impact on the systolic blood pressure
SUMMARY OUTPUT
Regression Statistics
1
Multiple R 0.16159796
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Multiple R 0.16159796
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Multiple R 0.16159796
R Square 0.0261139
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
R Square 0.0261139
Source - Another student's paper
R Square 0.0261139
Adjusted R Square 0.02601251
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Adjusted R Square 0.02601251
Source - Another student's paper
Adjusted R Square 0.02601251
Standard Error 3.98407837
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Standard Error 3.98407837
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Standard Error 3.98407837
Observations 9607
ANOVA
1
Df SS MS F Significance F
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Df SS MS F Significance F
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df SS MS F Significance F
Regression 1 4088.0545 4088.0545 257.54963 3.2438E-57
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Regression 1 4088.0545 4088.0545 257.54963 3.2438E-57
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Regression 1 4088.0545 4088.0545 257.54963 3.2438E-57
Residual 9605 152459.017 15.8728805
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Residual 9605 152459.017 15.8728805
Source - Another student's paper
Residual 9605 152459.017 15.8728805
Total 9606 156547.071
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Total 9606 156547.071
Source - Another student's paper
Total 9606 156547.071
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Source - Another student's paper
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 26.4067177 0.05408639 488.232228 0 26.3006969 26.5127384 26.3006969 26.5127384
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Intercept 26.4067177 0.05408639 488.232228 0 26.3006969 26.5127384 26.3006969 26.5127384
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Intercept 26.4067177 0.05408639 488.232228 0 26.3006969 26.5127384 26.3006969 26.5127384
CURSMOKE -1.3157466 0.08198639 -16.048353 3.2438E-57 -1.4764572 -1.155036 -1.4764572 -1.155036
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CURSMOKE -1.3157466 0.08198639 -16.048353 3.2438E-57 -1.4764572 -1.155036 -1.4764572 -1.155036
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CURSMOKE -1.3157466 0.08198639 -16.048353 3.2438E-57 -1.4764572 -1.155036 -1.4764572 -1.155036
In the third regression analysis, the Body Mass Index of patients is compared to the smoking patterns in the dataset's data.
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In the third regression analysis, the Body Mass Index of patients is compared to the smoking patterns in the dataset's data
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In the third regression analysis, the Body Mass Index of patients is compared to the smoking patterns in the dataset's data
From the analysis, the p-value was determined to be 3.2438E-57, which is below 0.05;
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From the analysis, the p-value was determined to be 3.2438E-57, which is below 0.05
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From the analysis, the p-value was determined to be 3.2438E-57, which is below 0.05
thereby, the null hypothesis is rejected.
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thereby, the null hypothesis is rejected
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thereby, the null hypothesis is rejected
Therefore, the smoking rate of an individual can be related to their Body Mass Index.
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Therefore, the smoking rate of an individual can be related to their Body Mass Index
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Therefore, the smoking rate of an individual can be related to their Body Mass Index
Smoking lowers the BMI of individuals by reducing their general body weight.
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Smoking lowers the BMI of individuals by reducing their general body weight
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Smoking lowers the BMI of individuals by reducing their general body weight
Smokers have a decreased appetite making them not improve on their bodies.
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Smokers have a decreased appetite making them not improve on their bodies
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Smokers have a decreased appetite making them not improve on their bodies
SUMMARY OUTPUT
Regression Statistics
1
Multiple R 0.08598698
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Multiple R 0.08598698
Source - Another student's paper
Multiple R 0.08598698
R Square 0.00739376
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
R Square 0.00739376
Source - Another student's paper
R Square 0.00739376
Adjusted R Square 0.00729042
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Adjusted R Square 0.00729042
Source - Another student's paper
Adjusted R Square 0.00729042
Standard Error 4.02218729
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Standard Error 4.02218729
Source - Another student's paper
Standard Error 4.02218729
Observations 9607
ANOVA
1
Df SS MS F Significance F
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Df SS MS F Significance F
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df SS MS F Significance F
Regression 1 1157.47172 1157.47172 71.5460746 3.104E-17
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Regression 1 1157.47172 1157.47172 71.5460746 3.104E-17
Source - Another student's paper
Regression 1 1157.47172 1157.47172 71.5460746 3.104E-17
Residual 9605 155389.6 16.1779906
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Residual 9605 155389.6 16.1779906
Source - Another student's paper
Residual 9605 155389.6 16.1779906
Total 9606 156547.071
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Total 9606 156547.071
Source - Another student's paper
Total 9606 156547.071
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
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Uploaded - MultivariateAnalysisofBodyMassIndex..docx
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Source - Another student's paper
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 25.7611868 0.04193192 614.357399 0 25.6789914 25.8433822 25.6789914 25.8433822
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Intercept 25.7611868 0.04193192 614.357399 0 25.6789914 25.8433822 25.6789914 25.8433822
Source - Another student's paper
Intercept 25.7611868 0.04193192 614.357399 0 25.6789914 25.8433822 25.6789914 25.8433822
DIABETES 1.72531564 0.20397439 8.45849127 3.104E-17 1.32548278 2.12514849 1.32548278 2.12514849
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DIABETES 1.72531564 0.20397439 8.45849127 3.104E-17 1.32548278 2.12514849 1.32548278 2.12514849
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DIABETES 1.72531564 0.20397439 8.45849127 3.104E-17 1.32548278 2.12514849 1.32548278 2.12514849
Lastly, diabetes is another aspect that is compared in the multivariate regression analysis.
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Lastly, diabetes is another aspect that is compared in the multivariate regression analysis
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Lastly, diabetes is another aspect that is compared in the multivariate regression analysis
After analyzing the data, it was established that the p-value was 3.104E-17, which is below 0.05, and hence the alternate hypothesis was accepted.
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After analyzing the data, it was established that the p-value was 3.104E-17, which is below 0.05, and hence the alternate hypothesis was accepted
Source - Another student's paper
After analyzing the data, it was established that the p-value was 3.104E-17, which is below 0.05, and hence the alternate hypothesis was accepted
Diabetes is a factor that relates to the Body Mass Index of patients ("Incorrect body mass index range in:
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Diabetes is a factor that relates to the Body Mass Index of patients ("Incorrect body mass index range in
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Diabetes is a factor that relates to the Body Mass Index of patients ("Incorrect body mass index range in
Does body mass index adequately convey a patient's mortality risk?"
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Does body mass index adequately convey a patient's mortality risk?"
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Does body mass index adequately convey a patient's mortality risk?"
2017).
1
An increase in the body mass index tends to make individuals highly susceptible to diabetes.
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An increase in the body mass index tends to make individuals highly susceptible to diabetes
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An increase in the body mass index tends to make individuals highly susceptible to diabetes
It is attributed to the increasing levels of sugar in the blood attributed to increased body weight.
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It is attributed to the increasing levels of sugar in the blood attributed to increased body weight
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It is attributed to the increasing levels of sugar in the blood attributed to increased body weight
Conclusion In conclusion, the Body Mass Index is an attribute related to the weight and height of an individual.
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Conclusion In conclusion, the Body Mass Index is an attribute related to the weight and height of an individual
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Conclusion In conclusion, the Body Mass Index is an attribute related to the weight and height of an individual
BMI is a factor in human beings that is determined by a variety of factors that are prevalent in the human body.
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BMI is a factor in human beings that is determined by a variety of factors that are prevalent in the human body
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BMI is a factor in human beings that is determined by a variety of factors that are prevalent in the human body
According to the multivariate analysis that was done on the Framingham Heart Study dataset, diabetes, systolic blood pressure, age, and smoking rate were determined to be the factors that are related to BMI.
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According to the multivariate analysis that was done on the Framingham Heart Study dataset, diabetes, systolic blood pressure, age, and smoking rate were determined to be the factors that are related to BMI
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According to the multivariate analysis that was done on the Framingham Heart Study dataset, diabetes, systolic blood pressure, age, and smoking rate were determined to be the factors that are related to BMI
These factors had a p-value of less than 0.05 in the multivariate regression that was conducted.
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These factors had a p-value of less than 0.05 in the multivariate regression that was conducted
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These factors had a p-value of less than 0.05 in the multivariate regression that was conducted
Thereby, the alternate hypothesis is accepted in this analysis, which states that BMI is related to the patient characteristics in the Framingham Heart Study.
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Thereby, the alternate hypothesis is accepted in this analysis, which states that BMI is related to the patient characteristics in the Framingham Heart Study
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Thereby, the alternate hypothesis is accepted in this analysis, which states that BMI is related to the patient characteristics in the Framingham Heart Study
References
1
Emel Önal, A.
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Emel Önal, A
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Emel Önal, A
(2019). undefined.
1
Body-mass Index and Health.
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Body-mass Index and Health
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Body-mass Index and Health
DOI:10.5772/intechopen.82142
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DOI:10.5772/intechopen.82142
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DOI:10.5772/intechopen.82142
Incorrect body mass index range in:
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Incorrect body mass index range in
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Incorrect body mass index range in
Does body mass index adequately convey a patient's mortality risk?
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Does body mass index adequately convey a patient's mortality risk
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Does body mass index adequately convey a patient's mortality risk
(2017).
1
JAMA, 309(5), 442.
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JAMA, 309(5), 442
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JAMA, 309(5), 442
doi:10.1001/jama.2013.15
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doi:10.1001/jama.2013.15
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doi:10.1001/jama.2013.15