Introduction to Health Statistics

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BHS220 Introduction to Health Statistics
Drawing inferences about population means and proportions
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Date
BHS220 Introduction to Health Statistics
A] Discuss what a hypothesis is. What is null and alternative?
A hypothesis is a proposition on the association between variables, with hypothesis testing then useful to establish the extent of this relationship. The correlation can be a positive relationship when variables move in the same direction or negative correlation when they the variables are indirectly related. The hypothesis allows one to test the viability of the prediction, and make decisions on the relationships between the variables (Bowers, 2009). The prediction goes beyond testing the expected outcome, and may offer a possible explanation on the expected results of tests.
Both the null and alternative hypotheses are identified whether to accept either of the two. The null hypothesis (Ha) assumes that no relationship or difference or effect exists between variables (Norman & Streiner, 2008). The null hypothesis states (H1) that a relationship exists between the variables, and the alternative hypothesis is the statement that one is trying to prove. If one rejects the null hypothesis, and then accepts the alterative hypothesis, this means that a relationship exists between the variables been studied. There is an assumption that the null hypothesis is true, when conducting hypothesis testing. In case where one disproves the null hypothesis when it is true then this is a type I error (false positive), while a type II error (false negative) occurs when one fails to reject a false null hypothesis (Peat & Barton, 2008).
B] Discuss hypothesis testing? How is it carried out?
Hypothesis testing is conducted through statistical test to determine whether there is evidence to support that the sample data has specific characteristics common in a population. The hypothesis testing takes into account the null and alternate hypotheses. Besides choosing the hypotheses tests, and stating the null hypothesis, testing involves setting a level of significance. The null hypothesis is the one being analyzed, while one also determines whether the alternative hypothesis is true. There is a need to verify the hypothesis made regarding a population with a degree of certainty.
After creating the null and alternative hypothesis one can then map the normal curve where possible to give a clearer picture about the re...