Statistical Analysis



Statistical Analysis

Part 1: Correlation/Regression and Chi Square Excel Worksheet

A: Correlation Table

 

SYS

DIAS

SYS

1

0.785369154

DIAS

0.785369154

1

B: Regression Equation Table

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.785369154

R Square

0.616804708

Adjusted R Square

0.606720621

Standard Error

7.291161488

Observations

40

ANOVA

 

df

SS

MS

F

Significance F

Regression

1

3251.665638

3251.655564

61.1661

2.00E-09

Residual

38

2020.119362

53.16103584

Total

39

5271.775

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

8.30787

7.64629

1.08625

0.28409

-7.17124

23.787

-7.17124

23.787

SYS

0.53355

0.06822

7.82088

2.00E-09

0.39544

0.67165

0.39544

0.67165

Considering the calculated values, the linear regression equation that uses the systolic pressure to predict the diastolic pressure is; DIAS = 8.30787 + 0.53355 * SYS.

C: Predicted diastolic pressure

In times of a case when a woman has a Systolic Blood Pressure of 100, the predicted diastolic pressure will be 8.30787 + 0.53355 * 100 = 61.66287.

Part 2: Exercise 27 Questions to be Graded

1. The independent variable in the mentioned figures is postnatal age as measured in hours. The dependent variables include the systolic blood pressure in Figure A, diastolic blood pressure in Figure B, and mean blood pressure in Figure C. The relationship between these variables as depicted in the Figures can be described as direct and positive, with an increasing trend. This suggests that with an increase in the independent variable, the corresponding dependent variable increases as well (LeFlore, Engle, & Rosenfeld, 2000, 37 - 50; Kleinman & Seri, 2012, 123 - 145).

2. The independent variable as depicted in the mentioned figures is postnatal age as measured in hours, while the dependent variables include systolic blood pressure for Figure A, diastolic blood pressure for Figure B, and mean blood pressure for Figure C. However, these figures demonstrate the relationship between variables for infants whose birth weight lied between 1001 to 1500 grams. The figures illustrate that the nature of relationship between the 3 different levels of blood pressure and postnatal age is directly proportional (LeFlore, Engle, & Rosenfeld, 2000, 37 - 50).

3. The outcomes in Figure 2 suggest that for every instance, the y intercept was significantly higher at p < 0.001, as compared to the comparable values of lines of best fit for infants whose birth weight was either greater than or equal to 1,000 grams. These results can be drawn with a thorough comparative observation of the y-intercepts as demonstrated in every graph of the mentioned figures (LeFlore, Engle, & Rosenfeld, 2000, 37 - 50; LeFlore & Engle, 2002, 415 - 420).

4. In the equation Y = 43.2 + 0.17 x, the y intercept is 43.2 whereas, the slope is 0.17. In this mentioned formula, “x” symbolizes the independent variable of the study, which is the postnatal age as measured in hours. The equation suggests that an increase in the value of x by one unit will lead to an increase in the Systolic Blood Pressure by 0.17 units (LeFlore, Engle, & Rosenfeld, 2000, 37 - 50).

5. As suggested in figure 2, the equation for SBP is 43.2 + 0.17 x. To calculate the value of Y or SBP for neonates =1,000 grams, when the magnitude of x which denotes the postnatal age, is 30 hours, we replace x with 30 (LeFlore, Engle, & Rosenfeld, 2000, 37 - 50); Y = 43.2 + 0.17 xY = 43.2 + 0.17 (30) Y = ...