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Health, Medicine, Nursing
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Case Study
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English (U.S.)
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Topic:

Understanding of Biostatistics

Case Study Instructions:

Using the materials in the module homepage and in the background section, please address the following:
Define and describe commonly used statistics for categorical and continuous variables to test for a statistically significant difference between two-samples or measures (e.g., chi-square, t-tests, binomial proportions, etc.). (1 page)
What is the difference between the one-sample t-test, the two-sample t-test, and the paired-sample t-test? (1 page)
Describe a type of study for each of these three types of t-tests, as well as the variable that is analyzed with each of the three forms of the t-test. (1 page)
References: At least two references from academic sources must be included (e.g., peer-reviewed journal articles). You may use any required readings from this module for your two references. Quoted material should not exceed 10% of the total paper (since the focus of these assignments is critical thinking). Use your own words and build on the ideas of others. When material is copied verbatim from external sources, it MUST be enclosed in quotes. The references should be cited within the text and listed at the end of the assignment in the References section (APA formatting recommended).
McDonald, J. H. (2014). Student’s t-test for one sample. In Handbook of biological statistics (3rd ed.). Sparky House Publishing, Baltimore, Maryland. Accessed at http://www(dot)biostathandbook(dot)com/onesamplettest.html
McDonald, J. H. (2014). Student’s t-test for two samples. In Handbook of biological statistics (3rd ed.). Sparky House Publishing, Baltimore, Maryland. Accessed at http://www(dot)biostathandbook(dot)com/twosamplettest.html
McDonald, J. H. (2014). Independence. In Handbook of biological statistics (3rd ed.). Sparky House Publishing, Baltimore, Maryland. Accessed at http://www(dot)biostathandbook(dot)com/independence.html
McDonald, J. H. (2014). Paired t-test. In Handbook of biological statistics (3rd ed.). Sparky House Publishing, Baltimore, Maryland. Accessed at http://www(dot)biostathandbook(dot)com/pairedttest.html
StatTrek. (2016). Hypothesis test for a mean. Retrieved from http://stattrek(dot)com/hypothesis-test/mean.aspx?Tutorial=Stat
StatTrek. (2016) Hypothesis test: Difference between means. Retrieved from http://stattrek(dot)com/hypothesis-test/difference-in-means.aspx?Tutorial=Stat
StatTrek. (2016). Paired sample t-test. Retrieved from http://stattrek(dot)com/hypothesis-test/paired-means.aspx?Tutorial=Stat

Case Study Sample Content Preview:

Biostatistics
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Biostatistics
Biostatistics entails the application of statistical concepts and principles to solve problems in public health and medicine. The statistical methods are applied in the testing of different variables in the hypothesis. Statistical techniques and tools are used in collecting, summarizing, analyzing, and interpreting data relating to a specified population. In medicine, various samples are tested to provide a better understanding of a specific problem. Different sample tests methods are applied when testing other variables. The paper examines the statistics used to test various variables while comparing one-sample, two-sample, and paired-sample t-tests.
Statistics used for categorical and continuous variables
Various statistics are used when testing categorical and continuous variables to obtain the difference between the variables. Under categorical variables, several statistics are used to test significant differences between measures. The commonly used statistics for categorical variables include the chi-square tests, t-tests, and Fisher's exact test (Daniel & Cross, 2018). The Chi-square is commonly used when analyzing categorical variables. Fisher's exact test is also a common alternative to the Chi-square test when evaluating statistical differences between two proportions. A one-sample, two independent samples, and paired sample t-tests are statistics applied in categorical variables to give significant differences between measures.
The analysis of variance statistics is used when a categorically independent variable and a dependent variable are to be tested to give a difference between the two factors. Binomial proportions also apply to the test of categorical variables. The continuous variables use various statistics, including the sample size, correlation statistic, ordinary least squares, logistic regressions, and range (Weissgerber et al., 2018). The techniques are used when making tests for continuous variables to obtain a statistical difference from the measures. The tests involve the evaluation of two samples, which should give a statistical difference for the population.
Difference between one-sample, two-sample, and paired-sample t-tests
In statistics, t-tests are used for making mean comparisons for different variables and give a hypothesis. A one-sample t-test determines the difference between an unknown population mean variable and a specific hypothesized value. The test is used for continuous data, for example, a random population sample. The test is applied where a null hypothesis is developed, and calculation is against an alternative hypothesis. The test considers one variable. When using the one-sample t-test, the assumption is that the population is usually distributed, variables are independent, continuous, and collected through random sampling from the population.
A two-sample t-test evaluates whether the population means for two samples are equal or not. The test is appli...
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