Good morning, can you please provide a detailed response to the information below. I know that the information is true based on researchers proven studies, but would like to have more dialogue to support what i provided.

On assumptions within statistical hypothesis testing. In my opinion, assumptions within statistical hypothesis testing act as instrument of logical deduction; fundamentally, each hypothesis test has parameters or a statistical scope. Moreover, assumptions allow researchers to make critical inference regarding a population sample. For example, most statistical tests assume the sample population will have normal distribution; consequently, statistical tests without a normal distribution create challenges for the researcher. Thus, in such a scenario the researchers may fail to accurately ascertain the appropriate null or alternative hypothesis. Additionally, assumptions in statistical hypothesis testing underpin the probability factors within the p-value. The p-value of a statistical test is the likelihood of failing to reject the null hypothesis. Assumptions, delineate the ingress and egress points within the statistical scaffolding, giving researchers an unambiguous and unequivocal statistically significant outcome based on acceptable measures of probability. Essentially, assumptions offer researchers a high degree of confidence when undertaking a statistical hypothesis test.

References

Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2019). Social statistics for a diverse society (9th ed.). SAGE Publications.

Salkind, N. J. (2000). Statistics for people who (think they) hate statistics. Thousand Oaks, Calif: Sage Publications, Inc.

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: SAGE Publications, Inc.