Contents
Can you use a t-test to compare percentages?
No, that’s perfectly fine and neccesary that you use absolute frequencies (counts) and not percentages, particularily when the sample sizes are not equal. There are cases where t-test may be (more-or-less) appropriate for percentages.
Can you do chi-square test with percentages?
Tip: The Chi-square statistic can only be used on numbers. They can’t be used for percentages, proportions, means or similar statistical values. For example, if you have 10 percent of 200 people, you would need to convert that to a number (20) before you can run a test statistic.
Can we compare 2 percentages?
First: work out the difference (increase) between the two numbers you are comparing. Then: divide the increase by the original number and multiply the answer by 100. % increase = Increase ÷ Original Number × 100. If your answer is a negative number, then this is a percentage decrease.
How do you know if a number is statistically significant?
The level of statistical significance is often expressed as a p-value between 0 and 1. 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.
How should one interpret the comparison of means from different sample sizes?
Book A is rated by 10,000 people with an average rating of 4.25 and the variance σ = 0.5. Similarly Book B is rated by 100 people and has a rating of 4.5 with σ = 0.25. Now because of the large sample size of Book A the ‘mean stabilized’ to 4.25.
Is the percentage of a population the same or different?
… Both percentages in the first cases are the same but a change of one person in each of the populations obviously changes percentages in a vastly different proportion. Should I take that into account when presenting the data?
Can a t test be used for different sample sizes?
You can use a t-test to assess if there are differences in the means. The different sample sizes don’t cause a problem for the t-test, and don’t require the results to be interpreted with any extra care.
How can I compare groups with unequal sample sizes?
I have two datasets containing Z-score data. However both of them are of highly different sizes, i.e one has 500 samples while the other has 4. I want to determine if the differences between the samples is statistically significant.