There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation are also required.
If the Z Score of a test is equal to zero then the raw score of the test is equal to the mean. Z Score = (Raw Score - Mean Score) / Standard Deviation
1.50
Vale verga ;)
The z score for the mean is always 0.
z-score of a value=(that value minus the mean)/(standard deviation). So if a value has a negative z-score, then it is below the mean.
Let your raw score be x and M the mean and S the standard deviation. The Z score for your specific x is Z=(x-M)/S So say your score is 80 (out of 100) and the mean is 70 and the standard deviation is 10. Then the z score for your 80 is: (80-70)/10=1 If on the other hand you got a 60, then the z score would be -1.
If the Z Score of a test is equal to zero then the raw score of the test is equal to the mean. Z Score = (Raw Score - Mean Score) / Standard Deviation
Yes.z = (raw score - mean)/standard error.Since the standard error is positive, z < 0 => (raw score - mean) < 0 => raw score < mean.
No.
z = (x - μ) / σ is the formula where x is the raw score and z is the z-score. μ and σ are the mean and standard deviations and must be known numbers. Multiply both sides by σ zσ = x-μ Add μ to both sides μ + zσ = x x = μ + zσ You calculate the raw score x , given the z-score, μ and σ by using the above formula.
There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation is also required.
A z-score requires the mean and standard deviation (or standard error). There is, therefore, not enough information to answer the question.
Without more information you cannot.
There is insufficient information in the question to answer it. To determine Z score, you need raw score, mean, and standard deviation. Please restate the question.
This question cannot be answered. You need the mean and standard deviation in order to compute a Z score for a Raw score. Please restate the question.
Go back to the basic data, estimate the sample mean and the standard error and use these to estimate the Z-score.
z = 0.5244, approx.