Respond to at least one of your colleaguesâ€ posts and explain the benefits and consequences of the â€œrelaxedâ€ level of significance. You are responding to the post below, its $5

Statistical significance determines a critical value of statistics and helps researchers decide whether or to reject the null hypothesis. On the other hand, meaningful statistical deals with the applicability of the statistical results in the real world (Laureate Education, 2016). Looking at the scenario research paper that claims a meaningful contribution to the literature based on finding statistically significant relationships between the predictor and response variable. The footnote contained gives the statement that the researchers conducted qualitative research using an exploratory method for the study and relaxed the level of significance to reject the null hypothesis to 10 levels. The researchers performed multiple regression and have settled on a model that contains several predictor variables that are statistically significant. The researchers try to prioritize which variable is most important to determine if the null hypotheses are rejected or not. It is important to note that the ability to evaluate the â€œhypothesisâ€ is a vital part and integral part of statistics on all levels to include but not limited to academic and professional research (Franfort-Nachmias & Leon-Guerrero, (2018, p. 361 ).

However for a hypothesis testing, you need to express your research hypothesis as a null and alternative hypothesis which are statements regarding the differences or effects that occur in the population. The null hypothesis statement is based on assumptions or probability that whatever you are trying to prove did not occur (that is a statement of no effect) while the alternate hypothesis states the opposite and is usually the hypothesis you are trying to prove to have some effect (that is a statement that an effect exists in the population). The hypothesis testing is therefore done to determine the level of statistical significance (effect) of variables expressed as the p-value given that you have your null and alternate statements. Therefore the probability of rejecting a null hypothesis if the null is false is its statistical power where there is a significant result and the likelihood of an effect in the population. More so the statistical power which is the value of alpha is often set equal to 0.05 which stipulates that a 5% chance that they will reject the null and this provides a relatively minimal risk of making a type I error (when the null hypothesis is true but you reject it erroneously).

Nevertheless since the traditional level of significance to reject the null hypothesis (0.05) was relaxed to 0.1, there is a 10% chance that they would reject the null hypothesis giving room for a less stringent level to be particularly confident in the result. Therefore â€œprobability values that range from 0.05 and 0.10, support evidence that lacks the ability to support reasoning to reject the null hypothesisâ€ (Franfort-Nachmias & Leon-Guerrero, 2018).

References

Laureate Education (Producer). (2016). Meaningfulness vs. statistical significance [Video file]. Baltimore, MD: Author.

Franfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social Statistics for a Diverse Society. 8th Edition. Thousand Oaks, CA: SAGE Publications.

Skill Builders:

Evaluating P Values

Statistical Power

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