Table Of Contents
  • Measures of central tendency
  • Mean reliability
  • Null hypothesis
  • Research hypothesis
  • Correlation coefficient
  • The null hypothesis 
  • T-test
  • One-way ANOVA

Measures of central tendency

The three calculations associated with the measure of central tendency are mean, mode, and median. Each of the three is used to capture the essence of how a typical entry or number in the data set should look like. The main idea is to compute a single value that should represent an entire element of the set.

Table 1: Cross-tabulation of Age group by Gender

                                Gender        
  Female   Male   Total frequency Total %
Age Group frequency % frequency %    
21-45 9 32.14% 3 13.64% 12 24.00%
46-65 8 28.57% 13 59.09% 21 42.00%
66-80 10 35.71% 5 22.73% 15 30.00%
>/=81 1 3.57% 1 4.55% 2 4.00%
Grand Total 28 100.00% 22 100.00% 50 100.00%

Table 2:  NIofH hypertension category by Age group

  age group      
  21-45 46-65 66-80 >/=81 Total frequency Total %
NIofH hypertension category frequency % frequency % frequency % frequency %    
 optimal <120/<80 4 33.33% 7 33.33% 5 33.33%   0.00% 16 32.00%
prehypertensive 120-139/80-89 5 41.67% 4 19.05% 3 20.00% 1 50.00% 13 26.00%
stage 1 = 140-159/90-99 3 25.00% 5 23.81% 5 33.33% 1 50.00% 14 28.00%
stage 2  =/>160/=>100   0.00% 5 23.81% 2 13.33%   0.00% 7 14.00%
Grand Total 12 100.00% 21 100.00% 15 100.00% 2 100.00% 50 100.00%

Table 3: NIofH hypertension category by Gender

  gender    
  Female Male Total frequency Total %
NIofH hypertension category frequency % frequency %    
 optimal <120/<80 7 25.00% 9 40.91% 16 32.00%
prehypertensive 120-139/80-89 9 32.14% 4 18.18% 13 26.00%
stage 1 = 140-159/90-99 8 28.57% 6 27.27% 14 28.00%
stage 2  =/>160/=>100 4 14.29% 3 13.64% 7 14.00%
Grand Total 28 100.00% 22 100.00% 50 100.00%

Table 4: hypertension lifestyle factors by Gender.

  gender    
  Female Male Total frequency Total %
can identify hypertension lifestyle factors frequency % frequency % frequency %
not at all 9 32.14% 5 22.73% 14 28.00%
 identifies some lifestyle risk factors 11 39.29% 12 54.55% 23 46.00%
 identifies all lifestyle risk factors 8 28.57% 5 22.73% 13 26.00%
Grand Total 28 100.00% 22 100.00% 50 100.00%

Table 4 presents the Cross-tabulation of the ability to identify hypertension lifestyle factors by Gender. We see from the table that 32.14% of females cannot identify hypertensive lifestyle risk factors at all while 39.29% can identify some and 28.57% can identify all hypertensive lifestyle risk factors. From the male category, 22.73% cannot identify hypertensive lifestyle risk factors at all while 54.55% can identify some and 22.73% can identify all hypertensive lifestyle risk factors. This means females (32.14%) are more likely not to know hypertensive lifestyle risk factors at all than males (22.73%) but less likely to know some hypertensive lifestyle risk factor than males (39.29% to 54.55%). (woo 2019). The implication of this result is that there is a need to increase awareness of risk factors of hypertension for females and studies can be carried out to answer the research question “Is there a significant association between the ability to identify hypertension risk factors and gender.

Summary Statistics

knowledge about client's target blood pressure  
Mean 2.76
Standard Error 0.1991
Median 2.5
Mode 2
Standard Deviation 1.40785
Sample Variance 1.982041
Kurtosis -1.13165
Skewness 0.355152
Range 4
Minimum 1
Maximum 5
Sum 138
Count 50
Table 6: Summary Statistics report of willingness to engage in self-care
willingness to engage in self-care  
Mean 6.72
Standard Error 0.31173
Median 7
Mode 7
Standard Deviation 2.204263
Sample Variance 4.858776
Kurtosis -0.64709
Skewness -0.35513
Range 8
Minimum 2
Maximum 10
Sum 336
Count 50

Mean reliability

The standard error measures the reliability of the mean. A small standard error means that the sample is a more accurate reflection of the actual population mean. The standard error for knowledge about the client's target blood pressure is 0.19 which is small this means that the sample mean is close to the population mean. Similarly, the standard error for willingness to engage in self-care is 0.31 which is also small denoting that the sample mean is close to the population mean. Moreover, we are 95% confident that the mean for knowledge about the client's target blood pressure will fall between 2.36 and 3.16. similarly, we are 95% confident that the mean willingness to engage in self-care is between 6.1 and 7.34 (Woo, 2019)

Null hypothesis

H0: there is no significant effect of willingness to engage in self-care on knowledge about the client's target blood pressure. The dependent variable is knowledge about the client's target blood pressure while the independent variable is a willingness to engage in self-care.

Research hypothesis

H1: there is a significant effect of willingness to engage in self-care on knowledge about the client's target blood pressure.

Correlation coefficient

The correlation coefficient (using correl function in excel) is 0.2541. This means there exist a weak positive relationship between knowledge about the client's target blood pressure and willingness to engage in self-care The coefficient of determination is given by the square of correlation coefficient

r^2=〖0.2541〗^2

r^2=0.0646

The coefficient of determination is 0.0646 and this means that 6.46% of the variation in knowledge about the client's target blood pressure is explained by a willingness to engage in self-care Scatterplot of knowledge about client's target blood pressure against the willingness to engage in self-care


A simple linear regression model was used to predict knowledge about the client's target blood pressure based on the willingness to engage in self-care. A insignificant regression equation was found (F(1,48)= 3.3133,P=0.0749), with an R2 of .0646. Participants’ knowledge about the client's target blood pressure is equal to 1.669+0.162willingness to engage in self-care. Participants' knowledge about the client's target blood pressure increased approximately 0.162 units for every additional unit of willingness to engage in self-care. willingness to engage in self-care is not a significant predictor of older adults’ actual activity level; p=0.0749.

The null hypothesis 

H0: there is no significant difference between female’s knowledge about the client's target blood pressure and men’s knowledge about the client's target blood pressure

The alternative hypothesis is given as

H1: female’s knowledge about the client's target blood pressure is significantly greater than men’s knowledge about the client's target blood pressure

The target population are nurses with expertise in hypertension management

The sample population is the 50 nurses sampled for this experiment

The independent variable is gender and is measured on a nominal scale with two levels (male and female.

The dependent variable is knowledge about the client's target blood pressure and is measured on an ordinal scale (0-5)

The test to be done is an independent t-test. This was done because the independent variable has two levels and they are from different samples (they are independent). The dependent variable is ordinal.

Step 2

The level of significance for the test is 0.05

Step 3

A one-tailed test is appropriate because the research question is directional. Since it asks if the female is more likely than the male, then it is directional and a one-tailed test is more appropriate.

Step 4

The independent t-test result is shown below

N Median Mode Range

Where n_1 is the observations for the first category andn_2is the degree of freedom for the second category. Therefore,

df=28+22-2

df=48

Step 6

The critical value fort for 0.05 level of significance and 48d.f. is 1.67

Step 7

The p-value at which the calculated test statistics fell under the curve is 0.47. comparing with the level of significance, it is greater which means the result is statistically insignificant, and thus, we do not reject the null hypothesis. We conclude that females are not more likely to have more knowledge about their target blood pressure than men.

T-test

An independent sample t-test was conducted to compare knowledge about the client's target blood pressure between females and males. There was no significant difference in knowledge about the client's target blood pressure or female (M=2.75, SD=1.48) and male (M=2.77, SD=1.34); t (48) =-0.056, p=0.478. These results suggest that females are not more likely to have more knowledge about their target blood pressure than men.

Using an independent t-test is not totally appropriate because the dependent variable is ordinal but not continuous, a Mann-Whitney U test would be more appropriate but the software used does not provide this functionality. Moreover, since this is a survey, the result might have been biased by response bias where the respondents did not give the correct response.

The implication of this result is that appropriate training must be directed towards both males and females and adequate awareness regarding the benefit of being aware of clients' blood pressure should be thought equally to males and females.

The null hypothesis is stated as:

H0: ability to identify lifestyle factors does not significantly affect willingness to engage in self-care

The research hypothesis is given as

H1: ability to identify lifestyle factors significantly affect willingness to engage in self-care.

The target population are hypertensive people

The sample population is the 50 participants used for this study

The independent variable is the ability to identify lifestyle factors and is measured on a nominal scale with three levels (cannot identify, can identify some, and can identify all).

The dependent variable is a willingness to engage in self-care and is measured on an ordinal scale (1-10)

The test to be done is the one -way ANOVA test. The rationale for this is that the dependent variables have more than two levels as required for the use of ANOVA. The dependent variable, though is ordinal, permits the use of one-way ANOVA.

Step 2

The level of significance is 0.05

Step 3

The test is a two-tailed test because the research question is not directional. i.e. is not looking at greater than or less than but strictly is their difference.

Step 4

The result of one-way ANOVA is presented below

N Median Mode Range

From the result, the test statistics is 3.73

Step 5

The degree of freedom of an F-test is given by (k-1,n-k) where k is the number of groups and n is the number of observations. Since we have 3 groups, k is 3 and we have 50 observations, so n=50. Therefore, the degree of freedom is (2,47).

Step 6

The critical value to be exceeded by the test statistics is 3.19.

Step 7

The level of significance at which the test statistics fall under the normal curve is 0.031 which is less than the level of significance of 0.05. this means that the result is statistically significant. Thus, we reject the null hypothesis and conclude that ability to identify hypertension lifestyle factors significantly affects the willingness to engage in self-care.

One-way ANOVA

A one-way ANOVA was conducted to determine if the willingness to engage in self-care is different between participants that cannot identify hypertensive lifestyle, those that can identify some, and those that can identify all. the average willingness to engage in self-care is the least for those that cannot identify hypertensive lifestyle(M=5.5, sd=2.34) followed by those that can identify all risk factors (M=6.77, sd=4.02) and it is the highest for participants that can identify some lifestyle risk factors (M=7.43, sd=1.97). This difference in mean is statistically significant (F(2,47)=3.73,p=0.031).

This result is based on a survey that may be subjected to response bias as participants may not give the correct response based on reasons known to them. Similarly, the sample size is small so that we cannot generalize the result to a larger population.

The implication of this result is that awareness of things or activities that constitute risk factors must be made available to people and the implications/benefits of engaging in self-care needed to be explained.