Table of Contents
- 1 How do you find the p-value from a test statistic and sample size?
- 2 How do you find the p-value of a sample statistic?
- 3 How is the p-value related to the test statistic?
- 4 How do you find P-value from test statistic in Excel?
- 5 When calculating a test statistic about the population proportion which distribution would you need to use?
- 6 How do you find the Z test statistic on a TI-84?
- 7 How do you get the p-value from a 1 sample t-test?
- 8 How do you calculate the test statistic for a single proportion?
How do you find the p-value from a test statistic and sample size?
If your test statistic is positive, first find the probability that Z is greater than your test statistic (look up your test statistic on the Z-table, find its corresponding probability, and subtract it from one). Then double this result to get the p-value.
How do you find the p-value of a sample statistic?
The p-value is calculated using the sampling distribution of the test statistic under the null hypothesis, the sample data, and the type of test being done (lower-tailed test, upper-tailed test, or two-sided test). The p-value for: a lower-tailed test is specified by: p-value = P(TS ts | H 0 is true) = cdf(ts)
What type of test should be used for a hypothesis test concerning a population mean if the sample size is large?
z-test
A z-test is a statistical test to determine whether two population means are different when the variances are known and the sample size is large. A z-test is a hypothesis test in which the z-statistic follows a normal distribution. A z-statistic, or z-score, is a number representing the result from the z-test.
The p-value, or probability value, tells you how likely it is that your data could have occurred under the null hypothesis. It does this by calculating the likelihood of your test statistic, which is the number calculated by a statistical test using your data.
How do you find P-value from test statistic in Excel?
As said, when testing a hypothesis in statistics, the p-value can help determine support for or against a claim by quantifying the evidence. The Excel formula we’ll be using to calculate the p-value is: =tdist(x,deg_freedom,tails)
What test statistic should be used?
Choosing a nonparametric test
| Predictor variable | Use in place of… | |
|---|---|---|
| Chi square test of independence | Categorical | Pearson’s r |
| Sign test | Categorical | One-sample t-test |
| Kruskal–Wallis H | Categorical 3 or more groups | ANOVA |
| ANOSIM | Categorical 3 or more groups | MANOVA |
When calculating a test statistic about the population proportion which distribution would you need to use?
normal distribution
We perform tests of a population proportion using a normal distribution when we can assume that the distribution is normally distributed. We consider this to be true if the sample proportion, p ‘ , times the sample size is greater than 5 and 1- p ‘ times the sample size is also greater than 5.
How do you find the Z test statistic on a TI-84?
Performing a Z-Test on the TI-83 Plus and TI-84 Plus. From the home screen, press STAT ▶ ▶ to select the TESTS menu. “Z-Test” should already be selected, so press ENTER to be taken to the Z-Test menu.
What does the p-value tell you in statistics?
The p -value tells you how often you would expect to see a test statistic as extreme or more extreme than the one calculated by your statistical test if the null hypothesis of that test was true.
How do you get the p-value from a 1 sample t-test?
Getting the p-value from a 1-sample t-test You test 35 cars and discover that the miles per gallon the cars get ranges from 14.4 to 28.8. After putting the data in the column MPG, you perform Minitab’s t-test (the menu command Stat > Basic Statistics > 1-Sample t, or the session command TTEST) and get these results: One-Sample T: C1
How do you calculate the test statistic for a single proportion?
The formula for the test statistic for a single proportion is, Z= (ṗ – p0)/√p0(1-p0)/n ṗ represents the number of people in the same population who have a particular characteristic of interest (for example, the number of women who are currently pregnant in the population). p 0 is the claimed value for the null hypothesis. n is the sample size.
Why is my p-value so low under the null hypothesis?
Because the test statistic is generated from your observed data, this ultimately means that the smaller the p -value, the less likely it is that your data could have occurred if the null hypothesis was true. Your calculated t -value of 2.36 is far from the expected range of t -values under the null hypothesis, and the p -value is < 0.01.