Table of Contents
- 1 What does p-value measure?
- 2 How do you know when to reject the null hypothesis?
- 3 How do you determine sample size for hypothesis testing?
- 4 What does t test tell you?
- 5 What are the 3 kinds of hypothesis?
- 6 How do you perform a hypothesis test?
- 7 How do you choose a sample size?
- 8 What is the percent error when using 2 significant figures?
- 9 Is it customary to keep a negative percent error?
- 10 How do you calculate the error in an experiment?
What does p-value measure?
The P value is defined as the probability under the assumption of no effect or no difference (null hypothesis), of obtaining a result equal to or more extreme than what was actually observed. The P stands for probability and measures how likely it is that any observed difference between groups is due to chance.
How do you know when to reject the null hypothesis?
After you perform a hypothesis test, there are only two possible outcomes. When your p-value is less than or equal to your significance level, you reject the null hypothesis. When your p-value is greater than your significance level, you fail to reject the null hypothesis. Your results are not significant.
What are the six steps of hypothesis testing?
Step 1: Specify the Null Hypothesis.
How do you determine sample size for hypothesis testing?
5 Steps for Calculating Sample Size
- Specify a hypothesis test.
- Specify the significance level of the test.
- Specify the smallest effect size that is of scientific interest.
- Estimate the values of other parameters necessary to compute the power function.
- Specify the intended power of the test.
- Now Calculate.
What does t test tell you?
The t test tells you how significant the differences between groups are; In other words it lets you know if those differences (measured in means) could have happened by chance. A t test can tell you by comparing the means of the two groups and letting you know the probability of those results happening by chance.
Can you accept the null hypothesis?
Null hypothesis are never accepted. We either reject them or fail to reject them. Failing to reject a hypothesis means a confidence interval contains a value of “no difference”. However, the data may also be consistent with differences of practical importance.
What are the 3 kinds of hypothesis?
The types of hypotheses are as follows: Simple Hypothesis. Complex Hypothesis. Working or Research Hypothesis.
How do you perform a hypothesis test?
There are 5 main steps in hypothesis testing:
- State your research hypothesis as a null (Ho) and alternate (Ha) hypothesis.
- Collect data in a way designed to test the hypothesis.
- Perform an appropriate statistical test.
- Decide whether to reject or fail to reject your null hypothesis.
What is a good sample size?
A good maximum sample size is usually 10\% as long as it does not exceed 1000. A good maximum sample size is usually around 10\% of the population, as long as this does not exceed 1000. For example, in a population of 5000, 10\% would be 500.
How do you choose a sample size?
Five steps to finding your sample size
- Define population size or number of people.
- Designate your margin of error.
- Determine your confidence level.
- Predict expected variance.
- Finalize your sample size.
What is the percent error when using 2 significant figures?
Multiply this value by 100\% to obtain the percent error: 0.0074074 x 100\% = 0.74\% (expressed using 2 significant figures ). Significant figures are important in science. If you report an answer using too many or too few, it may be considered incorrect, even if you set up the problem properly.
How do you calculate the percent error in statistics?
When keeping the sign for error, the calculation is the experimental or measured value minus the known or theoretical value, divided by the theoretical value and multiplied by 100\%. percent error = [experimental value – theoretical value] / theoretical value x 100\% Subtract one value from another.
Is it customary to keep a negative percent error?
For chemistry and other sciences, it is customary to keep a negative value. Whether error is positive or negative is important. For example, you would not expect to have positive percent error comparing actual to theoretical yield in a chemical reaction. If a positive value was calculated,…
How do you calculate the error in an experiment?
Subtract the theoretical value from the experimental value if you are keeping negative signs. This value is your “error.” Divide the error by the exact or ideal value (not your experimental or measured value). This will yield a decimal number.