# Question: What Does T Value Tell You?

## How do you interpret t test results?

Compare the P-value to the α significance level stated earlier.

If it is less than α, reject the null hypothesis.

If the result is greater than α, fail to reject the null hypothesis.

If you reject the null hypothesis, this implies that your alternative hypothesis is correct, and that the data is significant..

## How do you know if t statistic is significant?

So if your sample size is big enough you can say that a t value is significant if the absolute t value is higher or equal to 1.96, meaning |t|≥1.96.

## What does a Tukey test tell you?

The Tukey Test (or Tukey procedure), also called Tukey’s Honest Significant Difference test, is a post-hoc test based on the studentized range distribution. An ANOVA test can tell you if your results are significant overall, but it won’t tell you exactly where those differences lie.

## Why do we use Anova instead of t test?

The t-test is a method that determines whether two populations are statistically different from each other, whereas ANOVA determines whether three or more populations are statistically different from each other.

## What is a good t value?

Our t-value of 2 indicates a positive difference between our sample data and the null hypothesis. The graph shows that there is a reasonable probability of obtaining a t-value from -2 to +2 when the null hypothesis is true.

## What are the 4 steps of hypothesis testing?

Step 1: State the hypotheses. Step 2: Set the criteria for a decision. Step 3: Compute the test statistic. Step 4: Make a decision.

## How do you find P value from negative T?

If you have found a negative t value (t<0 ): multiply the t value you found by -1 (since table only works with positive values), resulting in a tpos. find row appropriate number of degrees freedom (df)

## How do you know if a critical value is positive or negative?

When you find the critical value, it should be negative since it is to the left of the mean. Whatever α is, subtract that from 1 to get the area to the left. When you find the critical value, it should be positive since it is to the right of the mean.

## What is difference between t test and Anova?

The t-test and ANOVA examine whether group means differ from one another. The t-test compares two groups, while ANOVA can do more than two groups. ANCOVA (analysis of covariance) includes covariates, interval independent variables, in the right-hand side to control their impacts.

## What does an Anova test tell you?

How does an ANOVA test work? ANOVA determines whether the groups created by the levels of the independent variable are statistically different by calculating whether the means of the treatment levels are different from the overall mean of the dependent variable.

## How do you calculate the T value?

Calculate the T-statistic Subtract the population mean from the sample mean: x-bar – μ. Divide s by the square root of n, the number of units in the sample: s ÷ √(n).

## What does a negative T value tell you?

Find a t-value by dividing the difference between group means by the standard error of difference between the groups. A negative t-value indicates a reversal in the directionality of the effect, which has no bearing on the significance of the difference between groups.

## What does the P value mean?

In statistics, the p-value is the probability of obtaining results at least as extreme as the observed results of a statistical hypothesis test, assuming that the null hypothesis is correct. … A smaller p-value means that there is stronger evidence in favor of the alternative hypothesis.

## What is T value and p value?

Consider them simply different ways to quantify the “extremeness” of your results under the null hypothesis. You can’t change the value of one without changing the other. The larger the absolute value of the t-value, the smaller the p-value, and the greater the evidence against the null hypothesis.

## What is p value formula?

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). … an upper-tailed test is specified by: p-value = P(TS ts | H 0 is true) = 1 – cdf(ts)