The most direct cause of the practice objected to in the source was that a landowners one and more workers then we’re arriving from Europe be investors thought English settlers were unwilling to work hard

john adams was the 2nd president of the united states.

explanation:

health care plans in the united states having high costs because they are focusing on providing quality programs for different groups of individuals. the quality of the service is based on money flow received from the members. without this investment, couldn't be possible a constant scientific searching to prevent death and illness caused because of low levels of health investigation. currently, the complaints are not about the highest cost, but about the coverage and benefits to access the necessary health services required by the members.  

besides, if a global health system is established the quality levels will fall down because of the standardized of the health. the access to care will increase but the quality will be low because it depends on the money invested.

a hypothesis is an expected answer to a question, usually based on some theory or prior research. hypothesis testing is a method of determining the viability of a hypothesis. let’s use the us presidential election as an example. there are many hypotheses (questions) about how people feel or whom they will vote for. the only way to know the 100% “truth” about the answers to these questions is to ask every single possible voter – something that is impossible, expensive, time consuming etc. instead, we take samples and use statistics to make “best guesses” about the answer to a particular hypothesis. we never know for sure if our conclusion is right at the time we accept/reject it, but these techniques, when used appropriately can get us close to the truth most of the time (which is a lot better than guessing, flipping coins or throwing darts to get answers).

the tricky part about hypothesis testing is that we have to think somewhat backwards about it – we have to test what is known as the “null hypothesis”. as an example, the hypothesis might be “obama is more popular than romney” while the null hypothesis is “there is no difference in popularity between obama and romney”. we focus on the null hypothesis because it tells us exactly what the expected value of our tests should be (obama popularity = romney popularity) and we can collect data and see if it comes out that way (see next section on “significance”). if it does, then we “accept the null hypothesis” and reject our original hypothesis. if the null hypothesis is disproven, we look at the data to see if our original hypothesis holds (obama> romney).