In an attempt to reduce the likelihood of a type ii error, the experimenter proposes to recruit a very large group of participants.
In statistical hypothesis testing, a Type I error is actually an incorrect rejection of the true null hypothesis (a.k.a. a "false positive" result or conclusion; e.g., "Innocent person convicted ing"). Rejection of one actually false null hypothesis (also called a "false negative" result or conclusion, e.g. "guilty party not convicted").
Many statistical theories revolve around minimizing one or both of these errors, but unless the outcome is determined by a known and observable causal process, either of these errors can be completely quantified. It is statistically impossible to eliminate You can improve the quality of the hypothesis test by choosing a lower threshold (cutoff) and changing the alpha (α) level. Knowledge of type I and type II errors is widely used in medicine, biometrics, and computer science.
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The correct answer is B.
The industrial revolution brought spectacular technological improvements that led to huge productivity gains in the manufacturing sectors that started to demand a very high number of employees. On the other hand, there was an excess of labor in the agricultural sector that, at those times, employed the majority of the population and it had also become highly unproductive.
Therefore, there was a movement of labor from the unproductive agricultural sector to the productive manufacturing sector. This movement was attached to the transfer of people from the countryside, where agricultural activities were located, to urban areas, where factories were located.
Answer:
"Facial-feedback hypothesis"
Explanation:
In psychology, the idea behind the facial-feedback hypothesis is that the facial expressions we make directly influence our emotional experiences.
The question mentions that Kathyrn seemed to enjoy the show more once she was prompted by her mom to smile while watching it. This would be a prime example of this theory. I hope this helped!
The statistical validity of frequency claims. false
Statistical validity can be described because the quantity to which drawn conclusions of a research look at may be taken into consideration correct and dependable from a statistical check. To obtain statistical validity, it's miles essential for researchers to have sufficient statistics and additionally pick the right statistical technique to analyze that records.
To gain statistical validity, researchers ought to have an adequate pattern size and select the proper statistical test to investigate the facts. shall we embrace you are analyzing a new drug for complications, and also you examine the outcomes of a experimental organization to those of a manipulate institution who failed to acquire the drug.
Concurrent validity evaluates the diploma to which a degree of a construct correlates with other simultaneous measures of that assemble. for instance, in case you administer exclusive intelligence assessments to the identical institution, there ought to be a strong, positive correlation among their rankings.
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