what is the difference between z value vs t value?
Z-value - tells you how many standard deviations from the mean your result is.
If z-value is positive, it indicates that the score is above the mean and if it's negative it indicates the score is below the population mean and if it's 0 it indicates the score is the same as the population mean.
Z-value is used when: the data follows a normal distribution when you know the standard deviation of the population and your sample size is above 30.
T-value - is used when you have a smaller sample <30 and you have an unknown population standard deviation.
Like z-value, t-value is also a conversion of individual scores into a standard form p-value is the probability that your null hypothesis will be rejected. The experimenter sets the level of significance and when the p-value < significance level, the null hypothesis is rejected.
So z-value and t-value measure the significant difference between the population means whereas p-value just gives us a result to reject or not to reject our null hypothesis that we set, it doesn't give you the statistic.