Essay:1. Is it possible for a process be in control and still produce nonconforming output.Explain. What are some corrective measures under these circumstances?

Nonconforming output A nonconforming output when not identified or controlled can lead to several…

Answered: 1. Is it possible for a process be in…

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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1- The manager of the purchasing department of a large saving and loan organization would like to develop a model to predict the amount of time (measured in hours) it takes to record a loan application. Data are collected from a sample of 30 days, and the number of applications recorded and completion time in hours is recorded. Below is the regression output: The degrees of freedom for the F test on whether the number of load applications recorded affects the amount of time are Regression Statistics Multiple R R Square Adjusted R Square Standard 0.9447 0.8924 0.8886 0.3342 Error Observations 30 ANOVA Significance F df SS MS F 25.9438 25.9438 232.2200 4.3946E-15 Regression Residual 28 3.1282 0.1117 Total 29 29.072 P-value Lower 95% Upper 95% Standard Error Coefficients t Stat 0.4024 0.1236 3.2559 0.0030 0.1492 0.6555 Intercept Applications Recorded 0.0126 0.0008 15.2388 0.0000 00109 0.0143 28, 1
8. Suppose that 30% of people taking a certain medication experience dizziness. A new formulation of the medication is created and tested in order to see if it decreases the incidence of dizziness. It is tested on 10 people, and only 1 of them experience dizziness. Do these result suggest that the new formulation is effective in decreasing the incidence of dizziness? (A) No. 1 is not significantly low since .121 is greater than .05. (B) Yes, because 1 is 66% less headaches than expected. (C) Yes, because 1 is 33% less headaches than expected. (D) Yes, because 1 is significantly low since it is less than 1.55 (E) No. 1 is not significantly low since .149 is greater than .05.
3. A psychology professor wants to know if stress in his statistics class is in anyway affected by a student's major and gender. Test to see if a students and major affects their stress level in the statistics course. Psychology Nursing Other 12 16 21 16 14 7 17 18 Male 12 15 22 8 15 23 9 17 18 EX? = 11275 16 20 23 10 17 28 7 21 28 Female 13 16 27 2 21 23 8 17 29 Critical Value=F(A) 3.32, F(B)4.17, F(AB) 3.32 Solve for the appropriate test statistic(s). Fill out a completed ANOVA Table on the answer sheet
2. Baldur is a big fan of salaries. He collects data on wages and the length of schooling the people had from 100 employees in a large company with the aim of creating a model that can predict wages by level of education (measured in the number of years in school after primary school). The employees with the lowest level of education in Baldur's data immediately entered the labor market after compulsory school leaving, while those with the highest level of education have completed 9 years of schooling after leaving compulsory school leaving. Baldur started by drawing the data and saw that the relationship is linear. He also calculated some fish sizes that can be seen below: standard Change average deviation salary 660020 150100 Education (year from primary school diploma) 5.5 2.2 He also calculated the correlation coefficient between salary and level of education (measured in the number of years in school from primary school exam) and obtained r = 0.55. a.) Find the equation regression…
In economics we are often faced with causal problems where the endogeneity arises because of simultaneity. A classic example is that if you are interested in estimating a demand curve, the issue is what you observe in the data are equli- birum and prices and quantity which is not only a function of demand but also a function of supply. In this excercise we will generalize the problem of simultaneity bias. Consider a situation where we are interested in the effect of Ti on Yi, i.e. obtaining a consistent estimate of α. But Yi also effects Ti. Let Xi be some exogenous covariates affecting both Yi and Ti. Let us imagine you have an exogenous variable Z which only effects Ti but does not directly effect Yi. In particular, consider the following structural equations: Yi = αTi+Xi′β+ui (1) Ti = ρYi+Xi′γ+Ziδ+νi (2) where E(ui | Xi,Zi) = 0 and E(vi | Xi,Zi) = 0 (a) Show why you cannot you use OLS to estimate α consistently in model 1? (b) Solve for the reduced form equation for Ti…
10.42) The retention of nitrogen in the soil is an important consideration in cultivation practices, including the cultivation of forests. Two methods for preparing plots for planting pine trees after clear-cutting were compared on the basis of the percentage of labeled nitrogen recovered. Method A leaves much of the forest floor intact, while method B removes most of the organic material. It is clear that method B will produce a much lower recovery of nitrogen from the forest floor. The question of interest is whether or not method B will cause more nitrogen to be retained in the microbial biomass, as compensation for having less organic material available. The percentage of nitrogen recovered in the microbial biomass was measured on six text plots for each method. Method A plots showed a mean of 12 and a standard deviation of 1. Method B plots showed a mean of 15 and a standard deviation of 2. At the 10% significance level, should we say that the mean percentage of recovered nitrogen…
What does February 2020’s actual grocery store sales value tell us about the strength of this model to extend past the ten years covered in the scatterplot?
1. A group of investigators wishes to explore the relationship between the use of hair dyes and the development of breast cancer in females. A group of 100 beauticians 40–49 years of age is identified and followed for five years. After five years, 20 new cases of breast cancer have occurred. Assume that breast cancer incidence over this time period for average American women in this age group is 30/100. We wish to test the hypothesis that using hair dyes decrease the risk of breast cancer. Compute p-value the answer is not 0.0021 a) 0 b) 47.6190
Please answer quickly and correctly The Samsung plant in Newberry is an assembly plant for home appliances. They assembly three types of appliances including washing machine, dishwasher, and oven (reference by W, R, and O). Each type of appliance is produced in a different assembly line which has some amount of output per day. Let’s imagine a quality engineer has gathered the following data in Table 1 from a small period of production, counting the number of products with defects and without defects. Let D indicates a defective product and ND indicates not defective. Washing Machine Dishwasher Oven: Defective 5 2 15 Not defective 63 86 45 Table 1: Number of products with and without defects by type a. Overall, what is the probability that a randomly selected product is defective? b. What is the probability that a randomly selected product is an oven? c. What is the probability that a product is defective, given it is an oven? d. What is the probability that a product is…
I have collected real data on the sale of a microwavable cup of soup across 20 different cities for the same time period (a month). The variables in the dataset are: Quantity sold in the city for that month: Measured in thousands of units Price: measured in dollars Average Income in the city: Measured in thousands of dollars Ads: Average number of ads run in stores for that city during that month. Price of a substitute product: measured in dollars Population of the city: measured in thousands of people The dataset is on Canvas and, using Excel or any other statistical software, please answer the following questions: 1. Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics. Graphs are welcome as well. 2. Take the logs of the variables, and estimate the demand function. a. Interpret the R-square. b. Interpret the coefficients for logP and logPsub c. Interpret the p-values associated with each independent…
Suppose when you add flexibility to your model by adding higher-order terms or more predictor variables that you begin to see the test or validation error (MSE or SSE evaluated on the test or validation set) begin to increase away from the training error. What kind of a problem are your models experiencing?
Is there a quick way to solve these kinds of problems with a TI-84? I spend a lot of time doing them by hand and I desperately need to speed up the process. Can you please walk me through the steps I need to do? please do not use excel, I will not have access to that.

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1. Is it possible for a process be in control and still produce nonconforming output. Explain. What are some corrective measures under these circumstances?