How does this passage show totalitarianism in the
soviet union? check all that apply
in this passage, a witness recalls a district communist
party conference in the ussr during stalin's rule.
at the conclusion of the conference, a tribute to comrade
stalin was called for. of course, everyone stood
the small hall echoed with "stormy applause, rising to an
ovation." for three minutes, four minutes, it was
becoming insufferably silly even to those who really
adored stalin. however, who would dare to be the first to
after all, nkvd men (the secret police were in
the hall applauding and watching to see who quit
some people refused to applaud.
the communist party was one of many political
parties in the ussr.
people were afraid to be the first to stop clapping.
the soviet government used fear and terror to
control its citizens
the government allowed people to have freedom
of speech and assembly
then, after eleven minutes, the director of the paper
sat down in his seat. and, oh, a miracle took
everyone else stopped dead and sat
that same night the factory director was arrested. they
easily pasted ten years ſin a labor camp) on him on the
pretext of something quite different. but after he signed
[his his interrogator reminded him:
intro
✓ done
do

the fraction 18/22 is equivalent to 9/11.

in decimal form if needed

this is a proper fraction once the absolute value of the top number or numerator (18) is smaller than the absolute value of the bottom number or denomintor (22).

the fraction 18/22 is equal to 18÷22 and can also be expressed in decimal form as 0.818182.

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).