Question

A mechanic wants to show that more than 44% of car owners do not follow a normal maintenance schedule.

Answer 1

Answer:

We need to conduct a hypothesis in order to test the claim that the true propotion is higher than 0.44, the system of hypothesis are .:  

Null hypothesis:$p \leq 0.44$  

Alternative hypothesis:$p > 0.44$  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)  

Step-by-step explanation:

Data given and notation

n represent the random sample taken

$\hat p$ estimated proportion of interest (owners who do not follow a normal maintenance schedule)

$p_o=0.44$ is the value that we want to test

$\alpha=0.05$ represent the significance level

z would represent the statistic (variable of interest)

$p_v$ represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the true propotion is higher than 0.44, the system of hypothesis are .:  

Null hypothesis:$p \leq 0.44$  

Alternative hypothesis:$p > 0.44$  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)  

Answer 2

Answer:H0: p≤0.44; Ha: p>0.44

Step-by-step explanation:

Let the parameter p be used to represent the proportion.

Remember that the null hypothesis is the statement already believed to be true and the alternative hypothesis is the statement that is trying to be shown. In this case, the mechanic is trying to show that more than 44% of people do not follow the maintenance schedule. So the alternative hypothesis is p>0.44. The null hypothesis is the opposite of this: p≤0.44.

Also, remember that the null hypothesis is always stated with some form of equality: equal (=), greater than or equal to (≥), or less than or equal to (≤). So we can double check that our answer above makes sense.