d
It depends on the population.Use t-test for a small population, N < 30; otherwiase, apply z-test or when N>=30.
erwtwertgrtewh
In a general t-test, there is no relationship between the members of one sample and the other. In a paired t-test they are connected in some way so that they are likely to give similar outcomes. This means that more of the difference between them can be attributed to the "treatment".
t test is used when- a) variables are studied b)the size of sample is a small one.(n<30) chi square test is studied when a) attributes are studied
t-test is the statistical test used to find the difference of mean between two groups
d
Yes, it is. The one sample t-test is a study of the parameter population-mean. You can also use the t-test to test for the difference between two population means (both parameters).
It depends on the population.Use t-test for a small population, N < 30; otherwiase, apply z-test or when N>=30.
Because under the null hypothesis of no difference, the appropriate test statistic can be shown to have a t-distribution with the relevant degrees of freedom. So you use the t-test to see how well the observed test statistic fits in with a t-distribution.
erwtwertgrtewh
In a general t-test, there is no relationship between the members of one sample and the other. In a paired t-test they are connected in some way so that they are likely to give similar outcomes. This means that more of the difference between them can be attributed to the "treatment".
t test is used when- a) variables are studied b)the size of sample is a small one.(n<30) chi square test is studied when a) attributes are studied
The null hypothesis of the independent samples t-test is verbalized by either accepting or rejecting it due to the value of the t-test. If the value is less than 0.05 it is accepted and greater than 0.05 is rejecting it.
independent sample t test
For goodness of fit test using Chisquare test, Expected frequency = Total number of observations * theoretical probability specified or Expected frequency = Total number of observations / Number of categories if theoretical frequencies are not given. For contingency tables (test for independence) Expected frequency = (Row total * Column total) / Grand total for each cell
no t test is similar to z test because t test ie used for unknown observation and z is for the medicne