Best to use a histogram i think! z scores can probably be used too however they seem more a method of how to transform outliers in workable scores.
If the Z-Score corresponds to the standard deviation, then the distribution is "normal", or Gaussian.
Z Score is (x-mu)/sigma. The Z-Score allows you to go to a standard normal distribution chart and to determine probabilities or numerical values.
There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation is also required.
z score = (test score - mean score)/SD z score = (87-81.1)/11.06z score = 5.9/11.06z score = .533You can use a z-score chart to calculate the probability from there.
Go back to the basic data, estimate the sample mean and the standard error and use these to estimate the Z-score.
If the Z-Score corresponds to the standard deviation, then the distribution is "normal", or Gaussian.
If a variable is Normally distributed then the z-score describes how far from the mean/median a particular observation is. For example, a z score of 1.96 implies that fewer than 0.025% of the observations will be at least that extreme.
There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation are also required.
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Z Score is (x-mu)/sigma. The Z-Score allows you to go to a standard normal distribution chart and to determine probabilities or numerical values.
There is not enough information to answer your question. To determine a Z-Score, the mean and standard deviation is also required.
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.
Assume the z-score is relative to zero score. In simple terms, assume that we have 0 < z < z0, where z0 is the arbitrary value. Then, a negative z-score can be greater than a positive z-score (yes). How? Determine the probability of P(-2 < z < 0) and P(0 < z < 1). Then, by checking the z-value table, you should get: P(-2 < z < 0) ≈ 0.47725 P(0 < z < 1) ≈ 0.341345
z score = (test score - mean score)/SD z score = (87-81.1)/11.06z score = 5.9/11.06z score = .533You can use a z-score chart to calculate the probability from there.
No, the Z-test is not the same as a Z-score. The Z-test is where you take the Z-score and compare it to a critical value to determine if the null hypothesis will be rejected or fail to be rejected.
There is insufficient information in the question to answer it. To determine Z-Score, you need raw score, which you gave, but you also need mean and standard deviation, which you did not give. Please restate the question.
Not all z-score tables are the same. You must know how to use the specific table that you have.