If you and everyone you knew (family), were sent to internment camps like the Japanese-Americans were during World War 2, and the military came to ask you to serve in the military and go risk your life fighting for the nation that just took
away all of your rights, freedoms, property and labeled you as a traitor, would you have volunteered to go fight for the
United States of America? Please explain your answer giving details as to why you would choose to fight or not
fight
for the U. S.A.

I NEED SOME OPINIONS

monitor contract compliance and results of forestry activities to assure adherence to government regulations.  

plan and supervise forestry projects, such as determining the type, number and placement of trees to be planted, managing tree nurseries, thinning forest and monitoring growth of new seedlings.  

establish short- and long-term plans for management of forest lands and forest resources.  

determine methods of cutting and removing timber with minimum waste and environmental damage.  

supervise activities of other forestry workers.

by the way there is no video here.

im going to go with b.

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).