In statistical methods, the significance level is a value that is used as a criterion for rejecting a null hypothesis. It used by first looking at the differences between the experimental results and from there the null hypothesis would be determined. Then, we assume that the null hypothesis is true, the probability of the differences is computed by using statistical tools. If the computed probability is less than or equal to the value of the significance level, then you conclude that the null hypothesis should be rejected and that the results are statistically significant. Usually, a significance level of 1% or 5% is used.
Answer:
See the explanation
Step-by-step explanation:
<h2>Analytic View:</h2>
If and event can occur in A number of way and fail in B number of ways, then probability of its occurrence is:

or probability of its failing is:

<h3>Example:</h3>
Rolling a number smaller than 3 in a dice.
A= 2 (1,2)
B = 4 (3,4,5,6)

<h2>Relative Frequency View:</h2>
Definition of Probability in terms of past performances (data). It can be taken as how often things happens divided by all outcomes.
<h3>Example:</h3>
A batter has 50 safe hits at 200 bats, which makes his batting average
which is the probability.
<h2>Subjective View:</h2>
When you define a probability due to personel beleif in the likelihood of an outcome. It involve no formal calculations and varies from person to person, depending on their past experience.
<h3>Example:</h3>
A person beleives that probability that the batter will hit safely in the next bat is 0.75
Y=6x-27...........(1)
y=4x-17...........(2)
By comparison
6x-27=4x-17
=> 2x=10 => x=5
Substitute x=5 into (1)
y=6(5)-27=3
Check:
y=4(5)-17=3 as well.
Answer:
C= 2.18x + 2.39
Step-by-step explanation:
Answer:
Rational
Step-by-step explanation:
This number is rational because it can be expressed as a ratio between two numbers.