In the research, 100 patients were treated using four different drugs to test their effects on their blood pressure. An equal number of 25 patients were treated with each drug, which were: placebo (assigned Control in this analysis), drug A, drug B, and drug A and B together. In the test various statistical tests were performed to draw the results. Bar graphs were drawn to display the descriptive statistics, Shapiro wilk test to investigate whether the variables were normally distributed, histograms to show blood pressure grouped by the type of drug in both Pre and Post BP. The scatter plot to check the correlation was also drawn.
In fig 1a the mean of all the patients was 65 years with a standard deviation of 10.9 (approximately 11 years). This means that many of the patients were aged between 54 76 years. The mean blood pressure of the total patients prior to the test was 140.65 mm Hg with a standard deviation of 16.516 mm Hg. This indicates that most patients had a blood pressure ranging from 124 mm Hg 156 mm Hg. (fig 2a). The above finding demonstrates that there was significant difference in the subject characteristics prior to the test since the descriptive statistics in age and pre Test BP could not much. Another difference is that most of the patients under the test had a pre-hypertension since their BP was over 120mm Hg and slightly higher than 140mm Hg. However, there was a similarity in that both figures (1a, 2a) a normal curve was perfectly placed meaning that both age and Pre Test BP were normally distributed. This qualifies the data to be investigated using various statistical tools. Figure 3a shows that there was a weak correlation between age and the BMI with slight increase in age being associated with slight increase in BMI.
The analysis of Histogram outlines the effects of the drugs. Figures (3b and 3c) shows that out of those that were tested with the placebo (control) drug, before the test 15 patients had a BP between 120-150mm Hg. After the test, the BP levels went even higher with more patients recording a BP of 120-180mm Hg. In the pre Test of the patients tested with Drug A, around 16 patients had a BP of between 130-150mm Hg. In the post test this figure went even higher with over 19 patients recording a BP between 130-160mm Hg and another 4 recording a BP above 160mm Hg.
Before the test 20 patients of those that tested with drug A and B , had BP between 120-160mm Hg. 4 patients had a BP of 160-180mm Hg with an exception of one patient who had 100mm Hg. After application of the drug A and B combined, the BP of many patients lowered with 24 patients having a BP of 90-150mm Hg. Out of these, 17 had a BP ranging from 120- 150mmHg. Before the test, 21 patients had a BP of 130-160mmHg out of those that were tested with drug B. Upon applying the drug the BP of 12 patients hiked to above 150mmHg with 6 patients recording a BP of over 180 mmHg.
The above findings clearly show that the combination of drug A and B lowered the BP of some of the patients. It was thus noted that the use of the drug was effective as noted in the results of 17 out of 20 patients who showed an improvement in their blood pressure. Comparing the BP level before the test showed a return to normalcy. It was thus effective to combine drug A and B to obtain the best results.
Bench press study: Data Analysis
The study consists of 50 trained power lifters. To obtain the results, several statistical procedures were carried out which included Regression analysis used in identifying the relationship between the bench press improvement, session volume and session intensity. The scatter plot to investigate the correlation effect of the lifters weight on the existing relationship between improvement, session volume and session intensity.
The average session intensity mean was found to be 85.046 with a standard deviation of 5.5745. Average session volume mean was 2931.002 with standard deviation of 612.6289 (table 1a). The improvement overall mean was 24.786 with a standard deviation of 5.9612.
From table 2a, there is an existing relationship between the three variables. The predictor variables which are session volume and session intensity, greatly affect the outcome dependent variable which is the bench press improvement. To identify which of the two predictors make the greatest contribution, we consider the standardized Beta coefficient column. The average session volume is the strongest predictor of the outcome since it has a higher Beta value (0.280) than the session intensity (0.148).
The Adjusted R Squared (0.45) suggests that the predictor variables could be used to explain 45% variance of the bench press improvement. (Table 1b). The model fitted to make future prediction can be deduced from table 2a which is:
Y= 3.320 + 0.159X1 + 0.003X2
Where X1 = average session intensity
X2 = average session volume
Y = the dependent variable
The scatter plot demonstrates that weight of the lifter affects the relationship as shown in Table 3a. The relationship changes rapidly when overweight is studied with change in weight associated with high improvement. The weight under 85 Kgs does not explain much the change in relationship. However, the Pearson moment correlation coefficient R2 = 0.2999 suggests that weight can only explain 29.99% variance of the relationship between improvement, session volume and session intensity.
It is thus prudent to conclude that there is a great correlation between the three variables since they all affect the bench press outcome. It is however noted that the average session volume is the strongest predictor of outcome due to its high Beta value compared to the session intensity.
Mean Std. Deviation N
Improvement 24.786 5.9612 50
Average Session Intensity 85.046 5.5745 50
Average Session Volume 2931.002 612.6289 50
Table 1a; showing descriptive statistics of improvement, session volume and intensity
Table 1b; model summary showing the regression of improvement, session volume and intensity.
Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations
B Std. Error Beta Zero-order Partial Part
1 (Constant) 3.320 14.315 .232 .818 Average Session Intensity .159 .152 .148 1.043 .302 .094 .150 .146
Average Session Volume .003 .001 .280 1.965 .055 .251 .276 .274
a. Dependent Variable: Improvement
Table 2a; showing the coefficients of the model in regression analysis to check the relationship between improvement, session volume and intensity.
Donnelly, R., & Kelley, W. M. (2009). The humongous book of Statistics Problems. Penguin.
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