In 1990, 1000 adults were randomly selected and each was asked if they smoked, 300
answered yes. In 2000, same question was asked to 2000 adults, 500 answered yes.
Assuming two samples are independent. Is there evidence that the proportion of smokers
was higher in 1990 than in 2000? Test at a = .05.

 The proportion of smokers was higher in 1990 than in 2000

Step-by-step explanation:

Solution

Recall that,

The total number of sample 1 (n1) = 1000

Total  sample 2 number  (n2) = 2000

The number of favourable events (X1) = 300

The number of favourable events (X2) = 500

so,

p₁ = X₁/n₁ = 300/1000 = 0.3

p₂ = X₂/n₂ =500/2000 =0.25

α = 0.05

We are interested in testing the hypothesis.

The  hypothesis (Null) >  H₀ : p₁ = p₂

Alternate hypothesis > H₁ : p₁ > p₂

Thus,

P = X₁ + X₂/ n₁ + n₂

P =300 + 500/1000 +2000

P =800/3000

=0.2667

Now,

Z₀ = P₁ - P₂/√ P (1 -P) (1/n₁ + 1/n₂)

Z₀ =  0.3 - 0.25/√0.2667  (1 - 0.2667) (1/1000 + 1/2000)

Z₀ = 0.4999999999999999/√ 0.2667 (0.7333000000000001) (0.001 +0.0005)

Then,

Z₀ = 0.4999999999999999/√0.00029335666500000004

Z₀ = 2.9193

so,

zα/2 = z0.05/2 =z0.025

zα/2 = 1.6448536269514722

Now, we apply the decision rule:

Decision Rule: Reject the null hypothesis if the statistic value test is higher than the critical value 1.6448536269514722

The statistic value, 2.9193 is greater than the critical value 1.6448536269514722,  then we will reject the null hypothesis.

Therefore, the proportion of smokers was higher in 1990 than in 2000

50*10 is greater

step-by-step explanation:

if you add the zero from 10 to 50, it will give you a bigger number.