The Gaussian (Normal) distribution is determined by two parameters: its mean and its variance. Each combination of these two parameters results in a different probability density function (pdf). Finding the probability based on raw scores would require values of the pdf relating to that particular combination of mean and variance. The pdf for the Gaussian distribution is not simple to calculate and it would be impossible to tabulate infinitely many of them. Instead, only the pdf for the Z-scores - the Standard Normal pdf - is tabulated. Any raw score is converted to a Z-score and the probability evaluated from the tables.
Yes.z = (raw score - mean)/standard error.Since the standard error is positive, z < 0 => (raw score - mean) < 0 => raw score < mean.
A z-score requires the mean and standard deviation (or standard error). There is, therefore, not enough information to answer the question.
There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation is also required.
Go back to the basic data, estimate the sample mean and the standard error and use these to estimate the Z-score.
A z-score is a means to compare rank from 2 different sets of data by converting the individual scores into a standard z-score. The formula to convert a value, X, to a z-score compute the following: find the difference of X and the mean of the date, then divide the result by the standard deviation of the data.
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.
There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation are also required.
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.
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.
A z-score requires the mean and standard deviation (or standard error). There is, therefore, not enough information to answer the question.
There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation is also required.
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.