Monday, July 7, 2008 ♥
Upon review of our research question and that is, is there any relationship between blood pressure before and after climbing fixed numbers of stairs? So our question is asking for any relationship between two variables.
Blood pressure before climbing stairs = scale data.
Blood pressure after climbing stairs = scale data.
We took a look at the decision path in choosing our statistical test. Here's how
We chose Pearson's R to be our statistical test to analyse our results. We know that when analysing a correlation question, we need to consider 2 factors which is the DIRECTION (positive or negative correlation) and STRENGTH:
First thing first, we need fulfil 4 assumptions when suggesting Pearson's R as our test.
- All observations must be independent of each other.
- The dependent variable should be normally distributed at each value of the independent variable.
- The dependent variable should have the same variablility at each value of the independent variable.
- The relationship between the dependent and independent variables should be linear
So we have came up with a scatter plot to check for linearity and homogenous variance ( assumption 3 and 4)
This is our before and after systolic's scatter plot.
In considering the 2 factors, direction and strength,
Direction = positive correlation. (The scatter appears to follow a general positive linear trend)
Strength = 0.094.
So you can see that there is a positive direction but very weak strength.
This is our before and after diastolic's scatter plot.
In considering the 2 factors, direction and strength,
Direction = positive correlation. (The scatter appears to follow a general positive linear trend)
Strength = 0.131
So you can see that there is a positive direction but very weak strength.
Compute Pearson's correlation co efficient
Diastolic
Systolic
So we set our Alpha value as 0.10.
From the systolic symmetric measure, we know that our p value is 0.10.
P(0.10) less than or = to alpha (0.10)
From the diastolic symmetric measure,we know that our p value is 0.05
p(0.05)less than or = to alpha (0.10)
Therefore, we reject our null hypothesis.
listened to the sweet sound @ 6:00 AM
