1 because if you split it into 4 it would be half of a half and 1 if half of a half! Hope that helps!
Reasonable Suspicion allows Police Officers to frisk a suspect, or even temporarily detain them, whereas Probable Cause allows Police Officers to issue a warrant, or even arrest the suspect. Probable Cause also allows grants Officers the power to search. Hope this helped!
-Twix
C is the correct answer.
Since the 1930s, the American Presidency has become its central institution. This was not always the case. Prior to FDR, the American Presidency had its strengths but was a co-equal branch with the Legislative and the Judiciary Branch.
FDR reshaped the Presidency during the Great Depression and World War II to make it the "first branch" of American government, or certainly the one that Americans perceive as the most important/powerful.
Answer:
One in four offspring (1/4)
Explanation:
A pink flower is heterozygous, let's assume As.
Thus crossing two heterozygous, the result will be;
Aa x Aa
AA, Aa, Aa, aa.
The phenotypic result will be , one red petal, two pink petal and one white petal
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.
