# Use the formula for finding a z score to determine the missing value in the following table round your answer to

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ated formula show the picture and box the answer. Also, Don't forget the unit. also, please please show detailed work including very small calculation such as plus and minus. please also clear all the steps so i can use it as example for the similar questions Thank you.
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our answer to two decimal places, if necessary. z x μ σ −0.67 26.40 30.3 ?
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- 1); I{x>1}, theta > 1. (a) Show that log Xi has an exponential distribution with a mean of 1/theta. (b) Find the form for a UMP test of H_0: theta <= theta_0 vs. H_a : theta > theta_0. (c) Give formula for nding the rejection region for a given value of alpha. Hint: use the result from (a) to fi nd the distribution of the test statistic. (d) Conduct the test in (b) with alpha = 0.05 and theta_0 = 1:5 using the dataset: {1.2, 2.4, 1.3, 1.7, 1.9}. (e) Find the form of a UMPU test for testing H_0 : theta = theta_0 vs. H_a : theta_0 != theta_0. (f) Use the data in (d) to conduct the test in (e) with alpha = 0.05 and theta_0 = 1.5.
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- 1); I{x>1}, theta > 1. (a) Show that log Xi has an exponential distribution with a mean of 1/theta. (b) Find the form for a UMP test of H_0: theta <= theta_0 vs. H_a : theta > theta_0. (c) Give formula for nding the rejection region for a given value of alpha. Hint: use the result from (a) to fi nd the distribution of the test statistic. (d) Conduct the test in (b) with alpha = 0.05 and theta_0 = 1:5 using the dataset: {1.2, 2.4, 1.3, 1.7, 1.9}. (e) Find the form of a UMPU test for testing H_0 : theta = theta_0 vs. H_a : theta_0 != theta_0. (f) Use the data in (d) to conduct the test in (e) with alpha = 0.05 and theta_0 = 1.5.
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- 1); I{x>1}, theta > 1. (a) Show that log Xi has an exponential distribution with a mean of 1/theta. (b) Find the form for a UMP test of H_0: theta <= theta_0 vs. H_a : theta > theta_0. (c) Give formula for nding the rejection region for a given value of alpha. Hint: use the result from (a) to fi nd the distribution of the test statistic. (d) Conduct the test in (b) with alpha = 0.05 and theta_0 = 1:5 using the dataset: {1.2, 2.4, 1.3, 1.7, 1.9}. (e) Find the form of a UMPU test for testing H_0 : theta = theta_0 vs. H_a : theta_0 != theta_0. (f) Use the data in (d) to conduct the test in (e) with alpha = 0.05 and theta_0 = 1.5.
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ution, regression, decision trees Past paper has 5 questions (attached), we will have 4. Complexity of questions will be reduced slightly for decision trees and regression. Visualisation question – written in word file or hand-written and scanned or photographed. Normal distribution: Sketch using online normal distribution visualisation applet (add notes around this to discuss if necessary) or sketch by hand and scan or photograph. For mathematical workings, use formulae sheet, copy, paste and adapt, or scan / photograph your workings and upload. Decision tree – use Office smart shapes, or sketch by hand and scan or photograph. If formulae are required, then use formula sheet, copy, paste and adapt. Regression – written in word file or hand-written and scanned or photographed. MCDA – written in word file or hand-written and scanned or photographed. Remember if they appear, decision trees and regression will be a little less technical than they have been in the past. (To allow more of a buffer with regards to time available to complete and upload). Visualisation and MCDA questions will be more general (strengths and weaknesses, key messages, make some recommendations). Exam questions will be set so as to minimise practical and logistical difficulties in uploading answers.
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risen to 28. Create the exponential formula for this situation. Use appropriate variables other than ‘x’ and ‘y’ in your formula. Create the graph of this formula in Excel and label the axes properly. Display your equation on the graph.
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1.AU MAT 120 Systems of Linear Equations and Inequalities Discussion

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