Topic 8.4 Statistical Inference, Statistical Significance and Hypothesis Testing

Topic 8.4 Statistical Inference, Statistical Significance and Hypothesis Testing

1. LO

   • The basic concepts of statistical inference and hypothesis testing, where we analyze the sample data to examine a relationship between variables and make inferences about the population.
     • Chi-Square (X2), confidence intervals (CI) and p-values
   • The issue of causation that assists us to interpret the results from a research studies.

2. Stat Inference

   • Makes use of information from a sample to draw conclusions (inferences) about the population from which the sample was taken.
   • Applies this process to datasets with calculated degrees of uncertainty
     • established that there is H1 or is not H0 association between the variables
       • interested in (independent and dependent), we have to test this association to find out if this is a statistically significant association.
   • Whole purpose of research
     • use data from a sample to make inferences about the whole population from which the sample was drawn because we are usually unable to conduct our research on the whole population.
       • the results from our analysis of this sample data, true (or statistically significant) for the whole population?”

3. Stat sign

   • specific meaning in research statistics and it come in two varieties:
   • 1. Statistical significance:
     • when the p-value is small enough to reject the null hypothesis of no effect
   • 2. Clinical importance:
     • when the effect size is large enough to be potentially considered worthwhile by patients.

4. Alternative Hypothesis (H1)

   • tentative theory, supposition (also known as the “hypothesis” quantitative researchers state at the beginning of the research process)
   • provisionally adopted to guide the practical steps we will use to conduct the research study.
   • hypothesis is statistically tested and potentially refuted in the analysis/interpretation step
   • we never state the hypothesis as an affirmative statement
     • always stated in the negative and is called the Null Hypothesis
   • If statistically proven, H1 states there IS a relationship between the IV and the DV

5. Null Hypothesis

   • typically proposes a general or default position, such as that “there is no relationship between two variables”
   • 1. typically proposes a general or default position, such as that “there is no relationship between two variables”
   • 2. That “there is no difference between the exposed and unexposed group” (i.e. in a cohort study)
   • 3. That “there is no difference between the cases and control groups” (i.e. in a case control study).

6. H0 states there is NO relationship between the IV and the DV