How do you tell if the null hypothesis rejects or fails?
There is a Wikipedia article on the topic. You can google "null hypothesis" without quotes, and it should be the first website that appears.
Can someone look at my question and my answer on this please
I have the question from my homework that someone can look at and Ive already done all the work so can someone check my answer and help me with it either being rejected or failed
To determine whether the null hypothesis rejects or fails, you need to perform a statistical hypothesis test. This involves the following steps:
1. State the null hypothesis (H0) and the alternative hypothesis (Ha): The null hypothesis typically represents the default belief or assumption, while the alternative hypothesis represents the opposing or alternative belief.
2. Select an appropriate significance level (α): The significance level is the threshold used to determine the level of evidence required to reject the null hypothesis. Common levels are 0.05 (5%) or 0.01 (1%).
3. Collect and analyze the data: Gather relevant data and perform statistical analysis depending on the nature of the study and the hypotheses being investigated.
4. Calculate the test statistic: The test statistic varies depending on the specific hypothesis test being conducted. Common test statistics include t-tests, z-scores, chi-square statistics, or F-tests.
5. Determine the p-value: The p-value is the probability of obtaining the observed test statistic (or more extreme) under the assumption that the null hypothesis is true. It quantifies the strength of evidence against the null hypothesis.
6. Compare the p-value to the significance level: If the p-value is less than or equal to the significance level (p ≤ α), there is sufficient evidence to reject the null hypothesis. This means the alternative hypothesis is supported.
7. Interpret the results: If you reject the null hypothesis, you can conclude that there is a statistically significant difference or relationship in the data. If the p-value is greater than the significance level (p > α), you fail to reject the null hypothesis. This means there is not enough evidence to support the alternative hypothesis.
It's important to note that failing to reject the null hypothesis does not prove it to be true. It simply suggests that the data you analyzed did not provide enough evidence to support the alternative hypothesis. The interpretation of the test results depends on the specific study and context.