8. A leading computer firm uses a sampling plan of n = 50 and c = 0 regardless of lot sizes. Construct the OC and AOQ curves. Graphically determine the AQL value for a = 0.05 and the AOOL value.
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- 1. Suppose that a set of samples x1, x2, ..., xn, all real numbers, are drawn i.i.d. from the same distribution. Also assume that this distribution is a Gaussian distribution, which can be represented as N(u, o²). Write a function that accepts a set of samples and returns the MLE estimator for u. NOTE: The code below will be evaluated by a Python 2.7 interpreter. def mle(samples): pass Run Reset Once your function is correct, your will receive a submission code that you should input into the answer field. Enter answer here 2. In the previous question, you were asked to write a function for an estimator of a parameter of a distribution. Is the result of this function, an estimator, a random variable? Yes NoThe difference between Linear Regression and Logistic Regression. Note: Please make in table and with your own wordWhat does it mean to measure centrality and the spread of a variable with at least two measures each? Using R
- Is this statement true? When outliers are important then it is important not to change the current minimum and maximum for normalization. False TrueThe value y (in 1982-1984 dollars) of each dollar paid by consumers in each of the years from 1994 through 2008 in a country is represented by the ordered pairs. (1994, 0.676) (1996, 0.638) (1998, 0.608) (2000, 0.584) (2002, 0.556) (2004, 0.528) (2006, 0.494) (2008, 0.461) (1995, 0.658) (1997, 0.622) (1999, 0.599) (2001, 0.568) (2003, 0.543) (2005, 0.509) (2007, 0.486) (a) Use a spreadsheet software program to generate a scatter plot of the data. Let t = 4 represent 1994. Do the data appear linear? O Yes No (b) Use the regression feature of the spreadsheet software program to find a linear model for the data. (Let t represent time. Round your numerical values to four decimal places.) y 3= (c) Use the model to predict the value (in 1982-1984 dollars) of 1 dollar paid by consumers in 2010 and in 2013. (Round your answers to two decimal places.) 2010 2013 24 Discuss the reliability of your predictions based on your scatter plot and the graph of your linear model for the data. Because the…Use R programming to solve the questions and include the pictures of the codes thanks
- A Ridge Linear Regression adds the sum of the squared values of the coefficients to the loss function to penalize large coefficients. Group of answer choices True Falseconsider a population where 30% is in poverty. If you randomly sampled 10 people, how many would you expect to be in poverty?An instructor who taught two sections of engineering statistics last term, the first with 25 students and the second with 40, decided to assign a term project. After all projects had been turned in, the instructor randomly ordered them before grading. Consider the first 15 graded projects. (a) What is the probability that exactly 10 of these are from the second section? (Round your answer to four decimal places.) (b) What is the probability that at least 10 of these are from the second section? (Round your answer to four decimal places.) (c) What is the probability that at least 10 of these are from the same section? (Round your answer to four decimal places.) (d) What are the mean value and standard deviation of the number among these 15 that are from the second section? (Round your mean to the nearest whole number and your standard deviation to three decimal places.) mean projectsstandard deviation projects (e) What are the mean value and standard deviation of…
- We estimate the following LRM for the relationship between COURSE_EVAL and AGE of the instructor: E(COURSE_EVAL | AGE) = 4.774 -0.2154 * log(AGE) where the AGE variable is transformed with the logarithmic function. Provide an interpretation of the coefficient estimate -0.2154.Assume an attribute (feature) has a normal distribution in a dataset. Assume the standard deviation is S and the mean is M. Typically: Group of answer choices, multiple choice: Then the outliers usually lie below -3*M or above +3*M Then the outliers usually lie above -3*S or below +3*S Then the outliers usually lie below -3*S or above +3*S Then the outliers usually lie above -3*M or below +3*MWrite code to define a K-NN regression model with K=5 and the neighbors are weighted by the inverse of their distance. [ ] # Write your code here