MEANS OF TWO SAMPLES (VARIANCES UNKNOWN) AND OBSERVED OBSERVATIONSGive the complete Test of Hypothesis 1. In semiconductor manufacturing, wet chemical etching is often used to remove silicon fromthe backs of wafers prior to metalization. The etch rate is an important characteristic in thisprocess and known to follow a normal distribution. Two different etching solutions have beencompared, using two random samples of 10 wafers for each solution. The observed etchrates are as follows (in mils per minute):Do the data support the claim that the mean etch rate is the same for both solutions? Inreaching your conclusions, use a=0.05 and assume that population variances are unequal.Solution 19.99.49.010.010.310.510.410.110.310.1Solution 210.810.110.310.510.010.010.210.310.410.3

Given : For solution 1 given data : 9.9,9.4,9.0,10.0,10.3,10.5,10.4,10.1,10.3,10.1…

Answered: rates are as follows (in mils per…

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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Test of Significance and their Test Statistics We have studied 2 different test statistics, z, and X2. Explain the similarities in; please go in-depth How each test statistic is calculated How each test statistic is used to determine if the sample statistic provides enough evidence against the null hypothesis to reject it.
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Relative to a balanced ANOVA an unbalanced ANOVA: Is typically more sensitive to non-uniform variances Has a smaller power All of these answers are correct. Does not have the same number of observations for each treatment An important difference between fixed- and random-effects models is: Fixed-effects models have no variance Random-effects models provide a better estimate of the variance Random-effects models are more reliable Fixed-effects models apply only to the selected treatments
Two-Sample Tests for Proportions What are the limitations of two-sample tests of proportions? Do these limitations present serious problems? Can the use of multiple confidence intervals for proportions overcome these limitations?
How will you test the difference between the variances? * No need to test differences. Standard error of the difference between means Standard error of the mean difference F-test T-test ANOVA single factor for uncorrelated samples
When we conduct a hypothesis test to compare two population means with known population standard deviations, which test statistic do we use? z test statistic t test statistic p test statistic Kai-square test statistic
true or false ? 1- If the large variance is combined with the small sample size and the small variance with the large sample size, this leads to a reduction in the error of the first type and the null hypothesis is accepted, then the decision is correct. 2- Test hypotheses and statistical estimation with a period of time achieve the same purpose 3- The strength of a statistical test increases with the increase in the level of statistical significance
Independent random samples were selected from two quantitative populations, with sample data given below. Using the p-value approach for the data given below, is there sufficient evidence to show that u, is larger than H, at the 1% level of significance? n, = n, = 50, x, = 125.1, x, = 123.8, S1 = 5.7, S2 = 6.9 In USE SALT Use the value of the test statistics 1.03 to calculate the p-value for the test. (Round your answer to four decimal places.) p-value = Enter a number. State your conciusion. O H, is rejected. There is sufficient evidence to indicate that the mean for population 1 is larger than the mean for population 2. O H, is rejected. There is insufficient evidence to indicate that the mean for population 1 is larger than the mean for population 2. O H, is not rejected. There is sufficient evidence to indicate that the mean for population 1 is larger than the mean for population 2. O H, is not rejected. There is insufficient evidence to indicate that the mean for population 1 is…
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