Two or More Sample Hypothesis Testing Paper
After rejecting the null hypothesis in the one sample hypothesis testing paper the team decides to adjust the data and analyze new thoughts and ideas (). The team considers the variables in the earlier study, population density and life expectancy, a worthy pursuit. The team’s efforts focus on the concluding thoughts from the earlier paper regarding similar geographical regions offering a more consistent pattern of correlation ().
The team decides to explore the correlation between the South American and European nations. The global demographic data set provides the needed information regarding population density and life expectancy from 13 ...view middle of the document...
The first step in the process was the thought of gathering and researching data involving a correlation between population density and life expectancy for the given countries (Doane & Seward, 2007). This thought pattern is consistent with the team’s further research. The second step relates to the stating of the new hypotheses (Doane & Seward, 2007). The team will offer two analyses from the data set regarding a sampling of 13 countries in Europe and 24 countries from South America (Lind, Marchal, and Wathen, 2008). The first analysis relates to population density and the second pertains to life expectancy. The first null hypothesis assumes equality when comparing the population densities of the two continents. The second null hypothesis presumes equality between the life expectancies of the same geographical locations. Both alternate hypotheses state just the opposite; the alternate hypotheses suggest a degree of variance between the South American and European nations regarding population density and life expectancy.
The third step relates to designing the experiment (Doane & Seward, 2007). The team will create a new spreadsheet from the data set specific to the European and South American countries. The team can also reuse the data involving the population density and life expectancy. In this research the team will separate the variables to distinguish a correlation between the two sets of countries. The use of proportions testing will allow the team necessary information to reject or fail to reject the hypotheses.
The fourth step in the process is to set up a decision rule (Doane & Seward, 2007). The purpose of this step is to explain whether the null hypotheses will be rejected or not rejected (Doane & Seward, 2007). A comparison test should establish either an equality or inequality within the research. Equality in the data for the two sets of countries will result in a failure to reject the null and any variance between the data supports a rejection of the null and a failure to reject the alternate hypothesis. The team considers a rejection of the null a basis for continued research as the alternate would only reflect inequality.
The fifth step includes obtaining necessary data (Doane &...