oThere will be some difference in the sample means, even when all of
the principles of experimental designs are utilized; this happens
because we are dealing with samples rather than populations.
•Random or chance error will be responsible for some difference in the means
even if the independent variable had no effect on the dependent variable.
•THE POINT IS THAT THE DIFFERENCE IN THE SAMPLE MEANS
REFLECTS ANY TRUE DIFFERENCEIN THE POPULATION MEANS,
PLUS ANY RANDOM ERROR.
•Inferential statistics give the probability that the difference between means
reflects random error than a real difference.
NULL AND RESEARCH HYPOTHESIS
•Statistical inference begins with a statement of the null hypothesis and a
research (or alternative) hypothesis.
Null Hypothesis: The hypothesis used for statistical purposes that the variables
under investigation are not related in the population, that any observed effect
based on sample results is due to random error.
(null hypothesis) : the population mean of the no-model group is equal to
the population mean of the model group
•Independent variable had no effect
• Used because it is very precise
oThe population means are exactly equal
oPermits us to know precisely the probability of the outcome of the
study occurring if the null hypothesis is correct.
oThe null hypothesis is rejected when there is a low probability that the
obtained results could be due to random error.
This is what is meant by statistical significance.
Statistical significance: Rejection of the null hypothesis when
an outcome has a low probability of occurrence (usually .05 or
less) if, in fact, the null hypothesis is correct.
•Significance is a matter of probability.
•Research Hypothesis: The hypothesis that the variables under
investigation are related in the population- that the observed effect based on
sample data is true in the population.
•(research hypothesis): The population mean of the no-model group is
not equal to the population mean of the model group
•Independent variable did have an effect.