The correct answer is Cause and effect
Explanation:
The text presented focuses on the economic crisis of 2008. In this, the author first refers to this event through a general statement "Many people are confused about why our economy went to shambles in 2008", and then explains the causes of the event. Additionally, to do this, the author enumerates the causes, this can be seen in "Second, banks would bundle these toxic loans...".
This means the general organization of this text is to mention an event and then explain the causes of it in detail. This only occurs in the cause and effect organization because this the only one that allows authors to explore the causes and/or effects of one or more events. According to this, the structure is cause and effect.
I believe that the best answer among the choices provided by the question is <span>B-in the future days, which we seek to make secure, we look forward to a world founded upon four essential human freedoms.</span>
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Well if something bad happened to him maybe its coming back more frequently and traumatized by it depending on what it is or if something had triggered those memories to found a way back,
I think the correct answer is the first option. The novel form is most closely related to poetry writing form. Novel are fictional stories that are lengthy while poetry can be fictional or non-fictional and are written relatively shorter. Both of them narrates a story in an artistic form.
"Critical region" redirects here. For the computer science notion of a "critical section", sometimes called a "critical region", see critical section.
A statistical hypothesis is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.[1] A statistical hypothesis test is a method of statistical inference. Commonly, two statistical data sets are compared, or a data set obtained by sampling is compared against a synthetic data set from an idealized model. A hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an idealized null hypothesis that proposes no relationship between two data sets. The comparison is deemed statistically significant if the relationship between the data sets would be an unlikely realization of the null hypothesis according to a threshold probability—the significance level. Hypothesis tests are used in determining what outcomes of a study would lead to a rejection of the null hypothesis for a pre-specified level of significance. The process of distinguishing between the null hypothesis and the alternative hypothesis is aided by identifying two conceptual types of errors (type 1 & type 2), and by specifying parametric limits on e.g. how much type 1 error will be permitted.
An alternative framework for statistical hypothesis testing is to specify a set of statistical models, one for each candidate hypothesis, and then use model selection techniques to choose the most appropriate model.[2] The most common selection techniques are based on either Akaike information criterion or Bayes factor.
Statistical hypothesis testing is sometimes called confirmatory data analysis. It can be contrasted with exploratory data analysis, which may not have pre-specified hypotheses.