Introduction
Statistical tests refer to different types of inferential analysis procedures used by researchers to calculate point estimates from data collected about a random variable of interest. The calculated point estimate shows the significance of the phenomenon under investigation to the null hypothesis. The null hypothesis is the general statement that is considered to be true about the parameter being investigated in relation to the general population. Research process and Statistical tests follow the convectional scientific method to ensure the process is credible, and results obtained are reliable (Sahu,2018).
The test to conduct is mainly determined by the nature of the data and the objective. The objective of my research is to compare two types of therapies that enhance ulcer management using ordinal data collected from 43, and it has a normal distribution. The independent variables in my research are two; Group A and Group B participants. Dependent variable refers to factors being manipulated, and in my research they are; visit in months, age, and duration since the last visit, which is given in months. A statistical test that can be used to determine if there is a significant difference between the mean of two samples includes ANOVA, Z-score, t-test, and Chi-square. The T-test will be a statistical test I will apply to determine if there is a significant difference between the two types of therapies based on data collected ('Information about Statistical Tests,' nd).
Delegate your assignment to our experts and they will do the rest.
Literature Review
A T-test is a statistical tool that uses continuous sample data with a normal distribution to calculate critical values for the hypothesis test. A T-test is therefore applicable when the actual population means and standard deviation are not known. There are three types of t-test; one sample test, independent t-test, and paired t-test. One sample t-test is used while comparing the calculated sample mean to hypothesized mean. A paired t-test is used when the data is obtained from repeated observations. Independent t-test, also known as a two-sample t-test, is used while analyzing two sets of data with an unequal mean (Ncss, nd).
Research Data
The total number of participants was 43 divided into two groups, with 19 participants in groups A and 24 were in group B. observation for each variable was made for all participants, and the average sample mean ( calculated. for each variable were as tabulated below.
| Variable | Group | Sample size | Calculated sample mean | Std Deviation | Std Error |
| Time since last visit (months) | A | 19 | 9.74 | 3.557 | 0.816 |
| B | 24 | 10.96 | 2.216 | 0.452 | |
| Age (Years) | A | 19 | 50.74 | 16.993 | 3.898 |
| B | 24 | 51.17 | 16.325 | 3.332 | |
| Duration of Disease | A | 19 | 1.32 | 0.478 | 0.11 |
| B | 24 | 1.25 | 0.442 | 0.09 |
Hypothesis Test
Research Problem
My objective is to investigate if the two therapies differ in ulcer management using the calculated sample mean and standard deviation.
Hypothesis
Null hypothesis: There is no significant difference between patients using therapy A and those using therapy B.
; = OR ( - = 0)
Alternative hypothesis: There is a significant difference between patients using therapy A and those using therapy B.
; ≠ OR ( - ≠ 0)
From the hypothesis designed as above I would generate three hypothesis to test for each dependent variable;
; = vs. ; ≠
; = vs. ; ≠
; = vs. ; ≠
Statistical Test - Independent t-test – two-tailed
Their test should be independent because participants and conditions in a group differ with those in group B and thus consider their mean unequal. The test is two-tailed since the alternative hypothesis has ≠ meaning mean difference can less than hence on the left side or greater than hence distributed on right side
Significant Level
Confidence level -95%
α = 0.05
Decision Rule
Negative Critical Test value < calculated test statistic >positive critical test value – reject the null hypothesis
Calculated p-value <critical p-value – reject null hypothesis
Limitations of t-Test
The T-test can only be used to analyses a maximum of two random variables. Multivariate analysis uses other approaches like ANOVA.
Results
| Treatment Group | N | Mean | Std Deviation | |
| Time of last (months) | A | 19 | 9.74 | 3.557 |
| B | 24 | 10.96 | 2.216 | |
| Age in Years | A | 19 | 50.74 | 16.993 |
| B | 24 | 51.17 | 16.325 | |
| Duration of Disease | A | 19 | 1.32 | 0.478 |
| B | 24 | 1.25 | 0.442 | |
| α | 0.05 | |||
| α/2 | 0.025 | |||
| df | 41 | |||
| CRITICAL P-VALUE | 0.05 | |||
| critical test value | -2.02 | |||
| time mean difference | 1.22 | |||
| age mean difference | -0.668 | |||
| duration mean difference | -0.036 | |||
| time test statistic | 1.171 | |||
| age test statistic | -0.185 | |||
| duration test statistic | -0.232 | |||
| time test p-value | 0.88 | |||
| age test p-value | 0.43 | |||
| duration test p-value | 0.49 |
Conclusion
Calculated p-values > Critical p-value (0.05)
We fail to reject the three null hypothesis.
References
Ncss. (nd). Two-Sample T-Test [pdf]. Retrieved from: https://ncss-wpengine.netdna-ssl.com/wp- content/themes/ncss/pdf/Procedures/NCSS/Two-Sample_T-Test.pdf
Sahu, S. (2018). MATH1024: Introduction to Probability and Statistics [pdf]. Retrieved from: http://www.soton.ac.uk/~sks/teach/2018_math1024.pdf
Some Critical Information about SOME Statistical Tests and Measures of Correlation/Association. (nd). Retrieved from:https://fycs.ifas.ufl.edu/swisher/6802_20/statistics.pdf
