The population proportion test is used to assess whether a given population proportion is significantly different from that of a hypothesized value P 0 . The alternative hypothesis focuses on the claim that the parameter is less than, greater than or equal to P 0. The Z score for the sample population is then calculated using the formula provided. The resulting figure (P value) is then used to prove either of the hypothesis.
Testing the equality of two population proportions requires one to assume the two population proportions are the same. That is if they are the same in terms of the proportions, they are then considered the same population. One first states the null and alternative hypotheses and determines the test statistic and p value.
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Testing hypothesis for population mean assesses claims about population mean. From a research question, the first step would be to determine the null hypothesis of the population mean against an alternative hypothesis that claims population mean is greater than, less than or equal to the p value.
The test for equality of two population means also follows the same as testing for population proportions. The only difference is that the test statistics are done with the respective means of the populations in relation to their standard deviation. The z value is then used to prove each hypothesis.
References
StatCrunch. (n.d.). Retrieved from https://www.youtube.com/playlist?list=PLBE055F65E43B4973
