Understanding Research Results: Statistical Inference

Generalizability - researchers can asses how confident they are that their results reflect what is true in the larger portion
Replicability - asses the likelihood that their findings would still occur if their study was repeated over and over
statistical validity - statistical methods that help ensure the accuracy of results

Samples and populations

researchers rarely study populations
- findings based on sample data
must describe sample dtata
- and make statements about populations
Inferential statistics tell if the results would match if we replicated the study over & over again
Tell if the differences in our sample means reflects a true difference in the

population means

Null & research hypotheses

Null hypothesis – population means are equal
- Observed difference is due to random error
- The independent variable had no effect
- Null hypothesis is very precise – means are exactly equal
  - Permits knowing precisely the probability of obtaining your results if the null hypothesis is correct
  - such precision not possible with the research hypothesis
Research hypothesis – population means are truly NOT equal
- The independent variable DID have an effect
H0 (null hypothesis): The population mean of the no-model group is equal to

the population mean of the model group

equal to the population mean of the model group

if you can determine that the null hypothesis is incorrect then you can accept the research hypothesis as correct
acceptance of the research hypothesis means the independent variable and an effect on the dependent variable