T score is usually used when the sample size is below 30 and/or when the population standard deviation is unknown.
You should think of a dependent t as being a single-sample t on the difference scores. This gives it 1 less than the number of differences as the df. Say you have before/after scores for 10 people. You have 20 scores, but the test is done on the differences, of which you have 10 and that means 9 df. You typically obtain df from n - 1, as you do in this case, you just need to be careful to think of this as the number of pairs and not scores.
You calculate the z-scores and then use published tables.
The Independent Samples T Test compares the mean scores of two groups on a given variable.
149
z=(x-mean)/(standard deviation of population distribution/square root of sample size) T-score is for when you don't have pop. standard deviation and must use sample s.d. as a substitute. t=(x-mean)/(standard deviation of sampling distribution/square root of sample size)
If, by SX, is meant the sum of the scores, then the answer is 48/4 = 12
Sorry this is meaningless. What exactly is the question?
T score is usually used when the sample size is below 30 and/or when the population standard deviation is unknown.
You should think of a dependent t as being a single-sample t on the difference scores. This gives it 1 less than the number of differences as the df. Say you have before/after scores for 10 people. You have 20 scores, but the test is done on the differences, of which you have 10 and that means 9 df. You typically obtain df from n - 1, as you do in this case, you just need to be careful to think of this as the number of pairs and not scores.
true
149
0.50
sum of scores: 24 mean of scores : 24/4 = 6 squared deviations from the mean: 9, 4,4,9 sum of these: 26 sample variance: 26/4 = 6.5
n= 25 scores from a population with mean =20
You calculate the z-scores and then use published tables.
Simple frequency distribution is a method of organizing large data sets into more easily interpreted sets. An example is organizing sample test scores by the individual scores.