In a random sample of 600 cars making a right turn at a certain intersection, 157 pulled into the wrong lane. Test the hypothesis that actually 30% of all drivers make this mistake at the given intersection. Use the level of significance. a) α = 0.05 b) α = 0.01

a)

The statistic value |Z| = 2.053 > 1.96 at 0.05 Level of significance

Null hypothesis is rejected

Alternative hypothesis is Accepted

Actually 30% of all drivers make not this mistake at the given intersection

b)

The test statistic value |Z| = 2.053 >2.576 at 0.01 Level of significance

Null hypothesis is Accepted

Actually 30% of all drivers make this mistake at the given intersection

Step-by-step explanation:

Step(i):-

Given Population proportion = 30% or 0.30

Given data In a random sample of 600 cars making a right turn at a certain intersection, 157 pulled into the wrong lane

sample proportion

Null hypothesis:- H₀: p = 0.30

Alternative  hypothesis : H₁:p≠0.30

Step(ii):-

a)

Test statistic

     Z =  -2.053

    |Z| = |-2.053| = 2.053

Level of significance = 0.05

Z₀.₀₅ = 1.96

The calculated value |Z| = 2.053 > 1.96 at 0.05 Level of significance

Null hypothesis is rejected

Alternative hypothesis is Accepted

Conclusion:-

Actually 30% of all drivers make not this mistake at the given intersection

b)

Given level of significance  = 0.01

Z₀.₀₁ = 2.576

The calculated value |Z| = 2.053 >2.576 at 0.01 Level of significance

Null hypothesis is Accepted

Actually 30% of all drivers make this mistake at the given intersection

answer: on graphs, the open and closed circles, or vertical asymptotes drawn as dashed lines us identify discontinuities.

as before, graphs and tables allow us to estimate at best.

when working with formulas, getting zero in the denominator indicates a point of discontinuity.

when working with piecewise-defined functions, check for discontinuities at the transition points where one piece ends and the next begins.

step-by-step explanation: