Given that, the 99% difference of the population means for the carbon content by two types of steel is between 0.0035 parts per million more by Steel Y to 0.0085 parts per million more by Steel X, compared to each other, respectively.

Given that, the 99% difference of the population means for the carbon content by two types of steel is between 0.0035 parts per million more by Steel Y to 0.0085 parts per million more by Steel X, compared to each other, respectively.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given rrepresents a significant linear correlation. Use a significance level of 0.05. r = -0.816, n =5 O A. Critical values: r=0.950, significant linear correlation OB. Critical values: r= ±0.878, significant linear correlation C. Critical values: r= ±0.878, no significant linear correlation O D. Critical values: r= ±0.950, no significant linear correlation
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Suppose IQ scores were obtained for 20 randomly selected sets of couples. The 20 pairs of measurements yield x = 101.16, y = 102.3, r= 0.810, P-value = 0.000, and y = 23.09+0.78x, where x represents the IQ score of the wife. Find the best %3D %3D %3D predicted value of y given that the wife has an IQ of 109? Use a significance level of 0.05. Click the icon to view the critical values of the Pearson correlation coefficient r. .... The best predicted value of y is . (Round to two decimal places as needed.) Critical values of the pearson correlation coefficient r NOTE: To test Ho: p = 0 against H,: p#0, reject Ho |if the absolute value of r is greater than the critical value in the table. a = 0.05 a = 0.01 4 0.950 0.990 0.878 0.959 0.811 0.917 0.754 0.875 0.707 0.834 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19 0.456 0.575 20 0.444 0.561 25 0.396 0.505 30 0.361 0.463 35 0.335 0.430 40…
I need help solving part a and b of the following question attached.
3. Suppose that the inside diameter of bulb lamp manufactured by a company are normally distributed with a sample of 200 bulb lamps, µ = 0.502 inches, and o = 0.005 inches. A bulb lamp will be considered defective if its diameter is less than 0.496 inches or greater than 0.508 inches. What is the percentage of defective bulb lamp produced by the company? What did the answer indicate?
Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r=0.543, n=25 O A. Critical values: r = ±0.396, no significant linear correlation OB. Critical values: r = ±0.487, significant linear correlation OC. Critical values: r = ±0.487, no significant linear correlation OD. Critical values: r = ±0.396, significant linear correlation
J In-shop othesis test for the difference between two population proportions 02562 2600368.qx3zqy7 Jump to level 1 The manager of a coffee shop is trying to determine if drive-through customers buy fewer items than customers who come into the shop. The manager randomly samples both populations and calculates the proportion of customers in each that buy three or more items. The results of the data collected are shown below. What are the population parameters? Y Pick Drive-through Successes 27 Successes What is the level of significance? Ex: 0.12 Observations 76 Observations 41 119 0.345 p-hat_1 0.355 p-hat_2 What is the null hypothesis Ho? Pick Confidence Level 0.1429 What is the alternative hypothesis Ha? Pick p-value Should Ho be rejected or does Ho fail to be rejected? Pick What conclusion can be drawn from the data? Pick evidence exists to support the claim that drive-through customers buy fewer items than in-shop customers. 2 p W
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