Answer:
a) See step by step explanation
b) z(s) = - 2.178
c) z(c) = - 1.64
d) We reject H₀
e) The proportion of drivers has decreased
Explanation:
We assume a survey with a random sample
Normality population
Size is big enough to use the approximation of binomial distribution to normal distribution
2019 sample:
sample size n = 963
drivers who admitted going more than 10 miles over the limit
x₁ = 315
p₁ = 315/963 p₁ = 32.71 % or p₁ = 0.3271 and q₁ = 1 - 0.3271
q₁ = 0.6729
Hypothesis Test:
a) Null Hypothesis H₀ p₁ = 36 %
Alternative Hypothesis Hₐ p₁ < 36 % or p₁ < 0.36
b) To calculate z(s) ; z(s) = ( p₁ - 0.36 ) / √ (p₁*q₁)/n
z(s) = ( 0.3271 - 0.36 ) / √ ( 0.3271* 0.6729)/963
z(s) = - 0.0329 / 0.0151
z(s) = - 2.178
c) we will use a confidence interval of 95 %. Then significance level α = 5 % α = 0.05 As the alternative hypothesis indicates we are going to develop a one-tail test
From z- table we find z(c) = - 1.64
d) Comparing z(s) and z(c) |z(s)| > |z(c)|
Then z(s) is in the rejection region for H₀ we reject H₀
e) we can support that the proportion of drivers has decreased since 2002