What does T value tell you in regression?
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.
How do you know if t-value 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.
Is a high t-value good or bad?
The greater the magnitude of T (it can be either positive or negative), the greater the evidence against the null hypothesis that there is no significant difference. The closer T is to zero, the more likely there isn’t a significant difference.
Is a high T value good?
Higher values of the t-value, also called t-score, indicate that a large difference exists between the two sample sets. The smaller the t-value, the more similarity exists between the two sample sets. A large t-score indicates that the groups are different. A small t-score indicates that the groups are similar.
Is the T value significant at the 0.05 level and why?
Because the t-value is lower than the critical value on the t-table, we fail to reject the null hypothesis that the sample mean and population mean are statistically different at the 0.05 significance level.
How is the t-statistic calculated in SPSS?
The single sample t-test tests the null hypothesis that the population mean is equal to the number specified by the user. SPSS calculates the t-statistic and its p-value under the assumption that the sample comes from an approximately normal distribution.
How is the t statistic related to standard error?
The t statistic is the coefficient divided by its standard error. The standard error is an estimate of the standard deviation of the coefficient, the amount it varies across cases.
What is the t statistic for null hypothesis?
The null (default) hypothesis is always that each independent variable is having absolutely no effect (has a coefficient of 0) and you are looking for a reason to reject this theory. The t statistic is the coefficient divided by its standard error.
When is the p value of T significant?
It is equal to the probability of observing a greater absolute value of t under the null hypothesis. If the p-value is less than the pre-specified alpha level (usually .05 or .01) we will conclude that mean is statistically significantly different from zero. For example, the p-value is smaller than 0.05.