Zusammenfassung der Ressource
Topic 8.4 Statistical Inference,
Statistical Significance and
Hypothesis Testing
- 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.
- 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?”
- 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.
- 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
- 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).
- H0 states there is NO relationship between the IV and the DV