In one hand he holds the small item called an Ankh, a symbol of eternal life.
In his other hand he holds a staff-like object, either a tool or a ceremonial staff known as a Was.
Answer:
That's so true! Thanks for giving this helpful advice ^-^
Explanation:
Answer:
Academic writing is the process of breaking down Ideas in a structural, focused manner in order to increase ones understanding on a particular thing.
Difference between academic writing and other types of writing
In academic writing you avoid using contractions ,for example can't ,wont; instead you use can not, will not.
The use of modal verbs in a formal way must be observed,example instead of "might" you can use "can"
In academic writing avoid using first person, example "I will"
Avoid use of slang and casual language.In Academic writting use of casual words and slang has been prohibited.
If you need any clarification or more explanation pls do mention in the comment section.I would like to help more
Hope this helps and if it does pls mark as branliest answer thx
Answer:3: If you go to the party I will come with you.
4: She will not be very happy if she did not get that new job.
5: If you come with us you will have a great time.
6: I will not wait for you if you are late.
7: That glass will break if you drop it.
8: We will help you if we find the time.
9: I will tell Claire the news if I see her.
10: We will sleep in the tent if it doesn’t rain
Explanation:
"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.
