8 to 16
2 to 4
13 to 26
5 to 10
6 to 12
Answer:
Step-by-step explanation:
In the two independent samples application, it involves the test of hypothesis that is the difference in population means, μ1 - μ2. The null hypothesis is always that there is no difference between groups with respect to means.
Null hypothesis: ∪₁ = ∪₂. where ∪₁ represent the mean of sample 1 and ∪₂ represent the mean of sample 2.
A researcher can hypothesize that the first mean is larger than the second (H1: μ1 > μ2 ), that the first mean is smaller than the second (H1: μ1 < μ2 ), or that the means are different (H1: μ1 ≠ μ2 ). These ae the alternative hypothesis.
Thus for the z test:
if n₁ > 30 and n₂ > 30
z = X₁ - X₂ / {Sp[√(1/n₁ + 1/n₂)]}
where Sp is √{ [(n₁-1)s₁² + (n₂-1)s₂²] / (n₁+n₂-2)}
(f-g)(x) = f(x) - g(x)
= (x^3 -2x+6) - (2x^3+3x^2-4x+2)
= x^3 -2x +6 -2x^3 -3x^2 +4x -2 . . . . distribute the negative sign
= (1-2)x^3 -3x^2 +(-2+4)x +(6-2) . . . . . combine like terms
(f-g)(x) = -x^3 -3x^2 +2x +4
