Karteikarten
Statistics
Karten in diesem Stapel (10)
- 1When do I use a one-sample t-test?If you are studying one group, use a one-sample t-test to compare the group mean to a standard value.
- 2When do I use a two-sample t-testIf you are studying two groups, use a two-sample t-test.
- 3When do I use a paired t-testIf you are studying one group, use a paired t-test to compare the group mean over time or after an intervention
- 4When do I use a two-tailed test?If you want to know only whether a difference exists, use a two-tailed test.
- 5One-sample t-test assumptions- Independent (values are not related to one another).
- Continuous.
- Obtained via a simple random sample from the population.
- Also, the population is assumed to be normally distributed. - 6How to perform the one-sample t-testFor the t-test calculations we need the average, standard deviation and sample size.
We now have the pieces for our test statistic. We calculate our test statistic as:
t = Difference/Standard Error
t = example: 3.07
The critical value of t with α = 0.05 and n-1 (example: 30) degrees of freedom is +/- 2.043
We compare the value of our statistic (3.07) to the t value. Since 3.07 > 2.043, we reject the null hypothesis that the mean grams of protein is equal to 20. We make a practical conclusion that the labels are incorrect, and the population mean grams of protein is greater than 20. - 7Testing for normalityThe normality assumption is more important for small sample sizes than for larger sample sizes.
Normal distributions are symmetric, which means they are “even” on both sides of the center. Normal distributions do not have extreme values, or outliers. You can check these two features of a normal distribution with graphs.
-> qq-plot - 8What if you know the underlying measurements are not normally distributed? Or what if your sample size is large and the test for normality is rejected?In this situation, you can use a nonparametric test. Nonparametric analyses do not depend on an assumption that the data values are from a specific distribution. For the one-sample t-test, the one possible nonparametric test is the Wilcoxon Signed Rank test.
- 9Result of a two-sided t-test: The software shows a p-value of 0.0046 for the two-sided test. What does that mean?A p-value of 0.0046 means there is about 46 chances out of 10,000. We feel confident in rejecting the null hypothesis that the population mean is equal to 20.
all the card info from: https://www.jmp.com/en_us/statistics-knowledge-portal/t-test/one-sample-t-test.html - 10What’s the key difference between the t- and z-distributions?The standard normal or z-distribution assumes that you know the population standard deviation. The t-distribution is based on the sample standard deviation.
Informationen
- Beschreibung
- Karteikarten am Statistics, erstellt von Katharina Kle am 01/11/2021.
- Erstellt von
- Katharina Kle
- Aufrufe
- 0
- Bewertung