Z-test refers to any statistical tests in which the test distribution of the statistics under the null hypothesis could be estimated using a normal distribution. This test is used to establish if there is a difference between the average of two populations and when the variance…
For example, z-test can be used in a research study that involves comparison diabetes prevalence between male and female adolescents in a certain city; this is because the population shall be very large.
A t-test is a hypothesis in statistics whereby the test statistics follows a t- distribution and the null hypothesis is congruent. In essence, the t-test can be assumed to establish whether two sample sets of data is significantly different from one another, and it is usually applied where the statistics being tested would have a normal curve distribution and the scaling term well known. The t-test examines the t-statistics as well as the level of freedom to establish a p-value, which can be utilised to determine if there is a difference in the population means (Senn, 2008).
The statistical significance in t-test indicates whether there is a difference between two sampled group and the mean mostly reflects the actual difference in the study population from which they were sampled. t-test can be utilised to establish if the slope of regression line has got significant difference from zero and to test null hypothesis when the difference between two answers have a mean value of 0 when measured on similar statistical unit. For example suppose, we are assessing the size of the prostate gland with cancer prior and post radiation. If the radiation was effective, then the tumour should decrease in size for several patients post treatment. This is often termed as paired ...
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