The correct answer is B: Rich Londoners are quick to bet huge sums of money to settle trivial arguments. This is because they were betting whether or not he would starve in a month. This is of course, not an actual concern and just an exaggeration, since rich people don't starve.
Answer:
A). A line graph from the National Oceanic and Atmospheric Administration showing average summer temperatures in the Southwest United States from 2001–2015.
Explanation:
As per the given details, the most significant source that would assist Evan in his research would be a 'line graph issued by the National Oceanic and Geographic Administration which display standard temperatures during the summer season in the SouthernWest part of the United States among the years 2001-15.' This would <u>assist him in analyzing the warming trends in that part for the last fifteen years and make reliable conclusions</u>. Thus, <u>option A</u> is the correct answer.
Answer:
“If you use your computer multiple times per day, it's best to leave it on. ... “Every time a computer powers on, it has a small surge of power as everything spins up, and if you are turning it on multiple times a day, it can shorten the computer's lifespan.”
Explanation:
please mark me brainliest or follow me pleeease.
"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.
The sentence whose style is most appropriate with respect to clarity and simplicity of language is the first one - For centuries, art admirers have been digging through records of the painting to figure out its meaning.
The other sentences use language that is quite complicated.
