Answer: The correct answer is : daily work hassles.
Explanation: Daily work stress especially results in jobs that involve responsibility for other people. At greater risk of exhaustion, a special education teacher who works with a population of children who have behavioral disorders could be found.
I believe at the time, St. Petersburg was founded in order to replace Moscow, which had been destroyed at the time.
The most expectable answer is socialization.
This term is used to describe the process in which people learn the values, norms, and beliefs of a particular society/culture.
Therefore, for this indian couple, their early and previously-arranged marriage is nothing unusual because they were taught that's the most common thing for (indian) people to do. And you, well, you were taught differently; probably: that is better to wait until you grow old enough, and are sufficiently independent, to support a household. So, you get a "cultural shock" by hearing about how this couple got married.
Answer: The 10th Amendment
Answer:
B) The chance of committing a Type I error changes from 0.01 to 0.05., E) The test becomes less stringent to reject the null hypothesis (i.e., it becomes easier to reject the null hypothesis), therefore. C) It becomes harder to prove that the null hypothesis is true and G) The chance that the null hypothesis is true changes from 0.01 to 0.05 are all correct answers
Explanation:
The alfa error or type I, refers to the probability error of rejecting the null hypothesis, when it is true, it is the chance of mistake when affirming that an association exists between two variables tested as a cause of an effect on something. i.e: H1: fast food is responsible for diabetes (this is working hypothesis), H0: red hair is responsible for diabetes (this is the null hypothesis). The beta error or type II is related to the size of the sample, it is the chance of accepting something (the null hypothesis) when it is false, depends mostly on having enough measures (or persons under study) so your hypothesis can be proven and be a real representation of the population under study. The statistical significance, namely the p value, can be narrow (p=0.01) or wide (p=0.05), it can be easily understand if we explain it in terms of percentage: you can have 99% (p=0.01) of certainty to affirm that the null hypothesis (the one that you do not believe is true, in the example, red hair as cause of diabetes) is actually wrong or 95% (p=0.05) of certainty to affirm that the null hypothesis (again, the one that you do not believe is true) is actually wrong.
