## What value is expected for the t statistic when the null hypothesis is true?

If the sample data equals the null hypothesis precisely, the t -test produces a t – value of 0. As the sample data become progressively dissimilar from the null hypothesis, the absolute value of the t – value increases.

## Which of the following is the correct null hypothesis for an independent t-test?

The null hypothesis for an independent samples t – test is (usually) that the 2 population means are equal.

## What is the correct null hypothesis for a repeated measures t-test?

Hypothesis Tests with the Repeated – Measures t (cont.) In words, the null hypothesis says that there is no consistent or systematic difference between the two treatment conditions. Note that the null hypothesis does not say that each individual will have a difference score equal to zero.

## Which of the following is a fundamental difference between a T statistic and a Z statistic Z-score )?

Which of the following is a fundamental difference between the t statistic and a z – score? The t statistic uses the sample variance in place of the population variance. If the sample variance increases, the estimated standard error will also increase.

## Which factor will increase the chances of rejecting the null hypothesis?

Using a higher significance level increases the probability that you reject the null hypothesis. However, be cautious, because you do not want to reject a null hypothesis that is actually true. ( Rejecting a null hypothesis that is true is called type I error.)

## Are t distributions always mound shaped?

The T distribution, like the normal distribution, is bell- shaped and symmetric, but it has heavier tails, which means it tends to produce values that fall far from its mean. T -tests are used in statistics to estimate significance.

## 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.

## What are the assumptions of t test?

The common assumptions made when doing a t-test include those regarding the scale of measurement, random sampling, normality of data distribution, adequacy of sample size and equality of variance in standard deviation.

## Why do we use t test?

A t – test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. A t – test is used as a hypothesis testing tool, which allows testing of an assumption applicable to a population.

## What are the 3 types of t tests?

There are three main types of t – test: An Independent Samples t – test compares the means for two groups. A Paired sample t – test compares means from the same group at different times (say, one year apart). A One sample t – test tests the mean of a single group against a known mean.

## What does P value mean?

A p – value is a measure of the probability that an observed difference could have occurred just by random chance. The lower the p – value, the greater the statistical significance of the observed difference. P – value can be used as an alternative to or in addition to pre-selected confidence levels for hypothesis testing.

## Which of the following is sometimes a serious problem with repeated measures designs?

It requires fewer subjects that other designs. It is easier to calculate the statistics. Which of the following is sometimes a serious problem with repeated measures designs? Small sample sizes can distort the results more than with other designs.

## What do T scores tell you?

A T – score is a standard deviation — a mathematical term that calculates how much a result varies from the average or mean. The score that you receive from your bone density (BMD or DXA) test is measured as a standard deviation from the mean.

## What is a good t statistic?

Generally, any t – value greater than +2 or less than – 2 is acceptable. The higher the t – value, the greater the confidence we have in the coefficient as a predictor. Low t -values are indications of low reliability of the predictive power of that coefficient.

## What does the t statistic tell you?

The t – value measures the size of the difference relative to the variation in your sample data. Put another way, T is simply the calculated difference represented in units of standard error. The greater the magnitude of T, the greater the evidence against the null hypothesis.