Calculating Probability of Cars' Expected Speed with Hypothesis Testing

In summary, we are trying to find the probability that the expected speed of 12 random cars is less than 77 km/h, given that the standard deviation is 10 km/h and the mean is 74 km/t. Using a significance level of 0.05, we calculate the z-statistic to be 1.039. Our hypotheses are H0: v < 77 and H1: v >= 77, and we must include all possibilities in our hypotheses. This is a one-tailed test.
  • #1
superwolf
184
0
If [tex]\sigma = 10 km/h[/tex] and [tex]\mu = 74 km/t[/tex], find the probability that we when measuring the speed of 12 random cars can conclude that the expected speed of the cars is less than 77 km/h. Use [tex]\alpha[/tex]=0.05 level of significance.

[tex]z = \frac{\bar{x}-\mu_0}{\sigma / \sqrt{n}} = \frac{77-74}{10/\sqrt{12}}=1.039[/tex]

Am I on the right track?
 
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  • #2
You should always state your hypothesis and then process to do the test statistic.

Also a Z statistic in this case, might be appropriate is the underlying population distribution is known to be normal. For this case maybe you can use it safely, because car speeds are usually normally distributed if the the simple random samplings were done correctly.

You should also state your conclusion, Do you Reject or Fail to Reject the null?
 
  • #3
[tex]
H_0: v=77
[/tex]
[tex]
H_1: v<77
[/tex]
 
  • #4
[tex]
H_0:\mu =77
[/tex]

[tex]
H_1:\mu <77
[/tex]

[tex]z_{observed} = 1.039[/tex]

What should I do now?
 
  • #5
Since you're dealing with a normal distribution, the probability of your null hypothesis is zero. Also, your null and alternate hypotheses should include all possibilities -- what if v > 77?

From the wording of the problem I think these are your hypotheses:
H0: v < 77
H1: v >= 77

With things set up this way, your test would be a one-tailed test.
 

1. What is a hypothesis?

A hypothesis is a proposed explanation for a phenomenon or question that can be tested through observation and experimentation.

2. What is the purpose of hypothesis testing?

The purpose of hypothesis testing is to determine whether there is enough evidence to support or reject a hypothesis based on the results of a study or experiment.

3. What are the steps involved in hypothesis testing?

The steps involved in hypothesis testing include: 1) stating the null and alternative hypotheses, 2) selecting a significance level, 3) collecting and analyzing data, 4) determining the test statistic and p-value, and 5) making a conclusion based on the results.

4. What is a p-value and how is it interpreted?

A p-value is the probability of obtaining a result at least as extreme as the one observed in the study, assuming that the null hypothesis is true. It is typically compared to the chosen significance level, and if the p-value is less than or equal to the significance level, the null hypothesis is rejected.

5. What is the difference between a one-tailed and two-tailed hypothesis test?

In a one-tailed hypothesis test, the alternative hypothesis is either greater than or less than the null hypothesis. In a two-tailed hypothesis test, the alternative hypothesis is that the parameter is not equal to the null hypothesis. The choice of one-tailed or two-tailed test depends on the research question and the directionality of the hypothesis.

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