How to calculate p value from t on TI 84?

How to calculate p value from t on TI 84?

To calculate the p value from t on a TI 84 calculator, you will need the t-value and the degrees of freedom of the t-distribution. Here’s how you can do it:

1. Press “2nd” and then “DISTR” to access the distribution menu.
2. Scroll down to “tcdf” and select it by pressing “ENTER”.
3. Enter the t-value and the degrees of freedom.
4. Press “ENTER” and you will see the p value.

It’s important to note that the p value is the probability of observing a t value as extreme as the one calculated, assuming the null hypothesis is true.

FAQs:

1. What is a p value?

A p value is a measure of the strength of evidence against the null hypothesis. It tells you how likely it is to observe your data if the null hypothesis is true.

2. What does a p value of 0.05 mean?

A p value of 0.05 means that there is a 5% chance of observing the data if the null hypothesis is true. It is a commonly used threshold for statistical significance.

3. How do you determine statistical significance from a p value?

If the p value is less than the chosen significance level (usually 0.05), then the results are considered statistically significant.

4. What is the relationship between t value and p value?

The t value tells you how much your sample mean differs from the population mean in standard error units, while the p value tells you the probability of observing a t value as extreme as the one you calculated.

5. Why is the p value important in hypothesis testing?

The p value helps researchers make decisions about the null hypothesis. If the p value is sufficiently small, it suggests that the null hypothesis should be rejected in favor of the alternative hypothesis.

6. What does a small p value indicate?

A small p value (typically less than 0.05) indicates strong evidence against the null hypothesis. It suggests that the observed data is unlikely to have occurred if the null hypothesis is true.

7. Can p values be negative?

No, p values cannot be negative. They range from 0 to 1, where a smaller p value indicates stronger evidence against the null hypothesis.

8. How do you interpret a p value of 0.1?

A p value of 0.1 means that there is a 10% chance of observing the data if the null hypothesis is true. It is generally considered to be not statistically significant.

9. Is a small p value always better?

Not necessarily. A small p value does not necessarily mean that the results are important or practically significant. It is important to consider the context of the study when interpreting p values.

10. What can influence the p value?

The p value can be influenced by the sample size, effect size, and variability of the data. Larger sample sizes tend to result in smaller p values.

11. How do you use the p value in hypothesis testing?

In hypothesis testing, the p value is compared to a predetermined significance level to determine whether the null hypothesis should be rejected. If the p value is less than the significance level, the results are considered statistically significant.

12. Can the p value alone determine the validity of a hypothesis?

No, the p value should be considered along with other factors such as effect size, sample size, and practical significance when evaluating the validity of a hypothesis.

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