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Find k such P(-k≤Z≤k)=0.7850 Help me with this problem, this is really getting me a headache, I tried doing it by tables (Because it's better), but it is really annoying and expense to doing it value by value, can someone explain to me how to do it in a logical form? please help me.
Solved 31 Given a standard normal distribution, find the
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To find the value k for P(k < Z) = .0089, we first need to find the complement of the probability, which is P(Z < k) = 1 - .0089 = .9911. Then, we look up the z-score in a standard normal distribution table or use a calculator. In this case, we find that k ≈ 2.36. Step 5/6 5. To find Z..0125, we look up the z-score in a standard normal.
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SOLVED Determine the value k, so that P(Z
Statistics and Probability questions and answers. 4) (3 pts) Given a standard normal distribution, find the value of k such that P (k < Z< -0.18) = 0.4197.
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Send us Feedback. Free Standard Normal Distribution Calculator - find the probability of Z using standard normal distribution step-by-step.
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Using the p-value to z-score calculator; What is a "Z score" P value to Z-score conversion table Using the p-value to z-score calculator. If you have a p-value statistic for a given set of data and want to convert it to its corresponding Z score this P to Z calculator will help you accomplish that. Simply enter the P-value and choose whether it was computed for a one-tailed or two-tailed.
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Sal used a simple shortcut. A z table indicates the proportion of the area of the distribution TO THE LEFT of a given z score. Given that normal distributions are by definition symmetric around their means, if we're looking for the area of just one tail in the positives, we can either subtract the proportion given by the z table from 1, or simply look at the corresponding negative z-score.
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SOLUTION: Find k such that p(z > k) = 0.85 How do I draw the standard normal distribution for this problem?
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Determine the conditional probability P (X>2.5 | X \leq 4) Suppose Z is the standard normal distribution. Illustrate with a sketch and find k such that: P (Z \leqslant k)=0.81 (Z ⩽ k) = 0.81. According to Chebyshev's theorem, the probability that any random variable assumes a value within 3 standard deviations of the mean is at least 8/9.
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