Because we fail to reject the null hypothesis, we conclude that there is not sufficient evidence to support a conclusion that the population mean is greater than 166.3 lb, as in the National Transportation and Safety Board’s recommendation.
Q. What causes a hypothesis to be rejected?
05. If there is less than a 5% chance of a result as extreme as the sample result if the null hypothesis were true, then the null hypothesis is rejected. If there is greater than a 5% chance of a result as extreme as the sample result when the null hypothesis is true, then the null hypothesis is retained.
Table of Contents
- Q. What causes a hypothesis to be rejected?
- Q. How do you reject a hypothesis?
- Q. Why do we reject the null hypothesis if/p α?
- Q. How do you reject the null hypothesis Chi Square?
- Q. What does P value signify?
- Q. What is a P value for a hypothesis test?
- Q. Why is p-value important?
- Q. How do you know if P value is significant?
Q. How do you reject a hypothesis?
Set the significance level, , the probability of making a Type I error to be small — 0.01, 0.05, or 0.10. Compare the P-value to . If the P-value is less than (or equal to) , reject the null hypothesis in favor of the alternative hypothesis. If the P-value is greater than , do not reject the null hypothesis.
Q. Why do we reject the null hypothesis if/p α?
a small p-value means: assuming H0 is true, it is extremely hard to obtain the observed result from our sample, which means: 1) Null hypothesis H0 is false OR 2) Our sample was not drawn from null population. Either way, we reject H0. That’s why when p < alpha, we reject H0.
Q. How do you reject the null hypothesis Chi Square?
If your chi-square calculated value is greater than the chi-square critical value, then you reject your null hypothesis. If your chi-square calculated value is less than the chi-square critical value, then you “fail to reject” your null hypothesis.
Q. What does P value signify?
The p-value, or probability value, tells you how likely it is that your data could have occurred under the null hypothesis. The p-value is a proportion: if your p-value is 0.05, that means that 5% of the time you would see a test statistic at least as extreme as the one you found if the null hypothesis was true.
Q. What is a P value for a hypothesis test?
In statistics, the p-value is the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is correct.
Q. Why is p-value important?
P-values can indicate how incompatible the data are with a specified statistical model. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
Q. How do you know if P value is significant?
The smaller the p-value, the stronger the evidence that you should reject the null hypothesis.
- A p-value less than 0.05 (typically ≤ 0.05) is statistically significant.
- A p-value higher than 0.05 (> 0.05) is not statistically significant and indicates strong evidence for the null hypothesis.
