Walden University Statistical Significance Discussion Response – Description
Statistical Significance
Statistical hypothesis testing is a procedure that allows us to evaluate hypotheses about population parameters based on sample statistics. According to Nachmias (2020), it requires several assumptions which include considerations of the level of measurement of the variable, the method of sampling, the shape of the population distribution, and the sample size. SPSS Statistics allows automatic testing of hypotheses without having to make a computation and check a cut point in a table in the back of a statistics book. The actual statistical significance is presented with the results. The p value refers to the probability that the result is due to chance, so smaller numbers are better. The standard in social sciences is usually .05; a result is deemed statistically significant if the p value is less than .05 (Wagner, 2020). According to the Amercian Statistical Association (2016), in light of misuses of and misconceptions concerning p-values, the statement notes that statisticians often supplement or even replace p-values with other approaches. These include methods “that emphasize estimation over testing such as confidence, credibility, or prediction intervals; Bayesian methods; alternative measures of evidence such as likelihood ratios or Bayes factors; and other approaches such as decision-theoretic modeling and false discovery rates.
Scenario
Based on the scenario, there were a few things that were incorrect, and it appears to be an old study. The word exploratory is dated and no longer being used. Also, the changes in the goal post were incorrect. Lastly the significance to reject the null hypotheses were relaxed at .10 level is incorrect. If p
The post Walden University Statistical Significance Discussion Response first appeared on .
