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Let's return to the example of the effect of telling stories on children's literacy skills.
Instead of defining all three groups, state that there is no significant effect of the variable: There is no significant effect of [independent variable] on [dependent variable].
For example, "There is no significant effect of socioeconomic status on children's interest in reading." They key identifying factor of experimental and quasi-experimental designs is that they examine the effect of a treatment on a dependent variable.
Correlational designs examine the relationship between two variables within the same group of individuals.
Research hypotheses for correlational designs should read as follows: There is no significant relationship between [variable 1] and [variable 2.] For example, there is no significant relationship between children's reading fluency and interest in reading.
When you have finished this step, review the Purposes and identify the matching Research Question or Hypothesis, and vis versa.
Once this has been completed, then it is time to start writing Chapter 3. For each purpose, write a matching Research Question OR Research Hypothesis.
" This would be analyzed by comparing the mean science test scores of males and females.
Imagine that the average score for males is 50.6 while the average score for females is 50.2.
Indeed, males scored higher, but only by 0.4 points on the test. There will virtually always be differences between two groups, although the differences can be very small.
The purpose of inferential statistics (e.g., t-tests, ANOVA, and ANCOVA) is to statistically determine whether the difference between two or more groups is significant enough to meaningfully say that there is a difference between these two groups of individuals.