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What are some of the limitations and assumptions of the t test?
Wiki User
∙ 11y ago
Assumptions of the t test and F test for independent means
The t test for independent means and the F test for independent means are based upon several assumptions about the nature of reality. If these assumptions are not true then the results of your analysis could be seriously flawed without you realizing it.
1) The scores in the various groups are independent. This means that one person's score does not affect any other person's score, they are independent of each other. An obvious violation of this assumption would occur if you had more than one score per person in your data set, as those scores come from the same person they are obviously connected in an important way (i.e. are not independent). The statistical analysis will be seriously flawed if the scores are not independent.
2) The populations are normally distributed. By 'populations' were are referring to the populations represented by each group in the experiment. The t and F tests were built upon the assumption that each population in the experiment is normally distributed. This assumption ends up only being important if you have a small number of scores in teach group. If N=30 in each group then you don't need to worry about whether or not this assumption is true. If you have reason to think that the populations are somewhat close to being normally distributed then you can have less than 30 scores in each group.
3) All the populations have the same variance. The t and F tests were also built upon the assumption that every population in the experiment have identical variances. This assumption ends up only being important if you have widely different N in each group. If you have roughly the same number of scores in each group then you don't need to worry about whether or not this assumption is true.
Limitations
The t and F tests for independent means only examine means, they have virtually nothing to say about individual scores. It is important to keep track of the fact that our conclusions are about means, not about individuals. So, if we run a study with gender as an independent variable, and get a statistically significant result, then we can say that the mean of males differs from the mean of females in terms of the dependent variable, but we cannot say that any particular male will have a higher or lower score than any particular female.
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∙ 11y ago
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What are the assumptions underlying the two sample t test?
The assumptions of a two-sample t-test are: Each sample come from a normally distributed population. Both populations have equal variances. The data are sampled independently from each population.
What are the assumptions underlying the two-sample t-test?
normal, SRS, independent normal, SRS, independent
What are the Limitations of the t-test in statistics?
Two limitations of a t-test are you can only use one factor at a time and you can only use two levels at a time. You have to watch out for the Type 1 error because it increases with simultaneous tests.
What is a t-test?
a t test is used inplace of a z-test when the population standard deviation is unknown.
What is t Test?
t-test is the statistical test used to find the difference of mean between two groups
What are the assumptions underlying the two sample t test?
The assumptions of a two-sample t-test are: Each sample come from a normally distributed population. Both populations have equal variances. The data are sampled independently from each population.
What are the assumptions underlying the two-sample t-test?
normal, SRS, independent normal, SRS, independent
What are the Limitations of the t-test in statistics?
Two limitations of a t-test are you can only use one factor at a time and you can only use two levels at a time. You have to watch out for the Type 1 error because it increases with simultaneous tests.
To conduct a t test for independent means ideally the populations should be both normally distributed and have the same?
The other assumptions are listed in the related link. The answer you are looking for is the same variance or standard deviation.
How is paired t-test different from a general t-test with two samples?
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".
What are the assumptions inherent in production setup costs ordering cost and carrying cost?
t
Is T test similar to Z test?
no t test is similar to z test because t test ie used for unknown observation and z is for the medicne
what are the answers for the test?
Some are T or F, others are A,B,C or D
Less than 400 t cells do you have aids?
I presume the '400 t cells' comes from some sort of test. The people who tested you should answer your questions, otherwise what is the point of the test?
What is a t-test?
a t test is used inplace of a z-test when the population standard deviation is unknown.
What is the t test used for?
The"t" test, (called the "small 't' test, to distinguish it from the large 'T' test) is a test for deviation from a known norm, using a smaller sample set than the one required by the large T test. It is said to have been developed by the head of quality control at the Guinness Brewery in Ireland.
What are the answers for driving test?
Some are T or F, others are A,B,C or D
