Suppose an analyst would like to use the beta distribution to simulatethe processing time of an activity. No field data are available for agoodness-of-fit test, but the analyst was told that the most likelyprocessing time is 18.6 min, with a minimum of 10 min and a maximumof 20 min. It is also known that the average time is 17.8 min. With thisinformation, the analyst can estimate the value of the shapeparameters as follows:απ(x-a)(2c-a-b)βẞ= a(b-x)(c-x)(b-a)(x-a)

solve this problem step by step to estimate the values of the shape parameters α and β.Given:- Most…

Answered: Suppose an analyst would like to use…

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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Linear regression is applied for a supervised learning problem with a training dataset with m=84 observations. The training dataset records, for each observation, n=D9 input features, as well as one output. One performs a t- test in order to decide whether the 7th input feature is significant for predicting the output. For this purpose, one computes the t-score: 07 to SE(Ô7) %3D The residual standard error (RSE) is used to estimate o. Under which t-distribution is one to interpret the valuer of the t-score above? (Note that a t-distribution is identified by the number of degrees of freedom).
In the manufacture of synthetic fiber, the fiber is often "set" by subjecting it to high temperatures. The object is to improve the shrinkage properties of the fiber. In a test of 25 yarn specimens, the relationship between temperature in °C (x) and shrinkage in % (y) was squares was Ey; - 9 = 57.313, and the estimated error variance was s =" 0.0670. Compute the coefficient of determination ?.
It has long been accepted by the general public that normal body temperature is 98.6 degrees. A group of 20 randomly selected adults was selected and their body temperatures were taken. Of them, 14 had a body temperature of less than 98.6, 3 had body temperatures of 98.6 and 3 had body temperatures of more than 98.6 degrees. At α =0.05, test the claim that the median body temperature is less than 98.6 degrees. A. Determine the test statistic. B. Determine the critical value.
For 50 randomly selected speed dates, attractiveness ratings by males of their female date partners (x) are recorded along with the attractiveness ratings by females of their male date partners (y); the ratings range from 1 to 10. The 50 paired ratings yield x = 6.2, y = 6.0, r=-0.209, P-value = 0.144, and y=7.48 -0.239x. Find the best predicted value of ŷ (attractiveness rating by female of male) for a date in which the attractiveness rating by the male of the female is x = 4. Use a 0.05 significance level. The best predicted value of y when x = 4 is (Round to one decimal place as needed.) C
A random sample of 160 car purchases are selected and categorized by age. The results are listed below. The age distribution of drivers for the given categories is 18% for the under 26 group, 39% for the 26-45 group, 31% for the 45-65 group, and 12% for the group over 65. Find the critical value xa to test the claim that all ages have purchase rates proportional to their driving rates. Use α = 0.05. Round to three decimal places. Age Under 26 26-45 46-65 Over 65 66 39 30 Purchases O A. 11.143 OB. 7.815 O C. 6.251 OD. 9.348 25
As the population ages, there is increasing concern about accident-related injuries to the elderly. An article reported on an experiment in which the maximum lean angle—the farthest a subject is able to lean and still recover in one step—was determined for both a sample of younger females (21–29 years) and a sample of older females (67–81 years). The following observations are consistent with summary data given in the article: YF: 28, 34, 32, 27, 28, 32, 31, 35, 32, 28 OF: 19, 14, 21, 13, 12 Does the data suggest that true average maximum lean angle for older females (OF) is more than 10 degrees smaller than it is for younger females (YF)? State and test the relevant hypotheses at significance level 0.10. (Use ?1 for younger females and ?2 for older females.) H0: ?1 − ?2 = 10Ha: ?1 − ?2 > 10H0: ?1 − ?2 = 10Ha: ?1 − ?2 < 10 H0: ?1 − ?2 = 0Ha: ?1 − ?2 > 0H0: ?1 − ?2 = 0Ha: ?1 − ?2 < 0 Calculate the test statistic and determine the P-value. (Round your test…
To the Internal Revenue Service (IRS), the reasonableness of total itemized deductions depends on the taxpayer's adjusted gross income. Large deductions, which include charity and medical deductions, are more reasonable for taxpayers with larg given level of income, the chances of an IRS audit are increased. Data (in thousands of dollars) on adjusted gross income and the average or reasonable amount of itemized deductions follow. Adjusted Gross Income Itemized Deductions ($1,000s) 22 ($1,000) 9.6 27 9.6 32 10.1 48 11.1 65 13.5 85 120 15.7 25.5 (a) Develop a scatter diagram for these data with adjusted gross income as the independent variable. 30 25 20 15 10 5 30 25 20 15 10 5+ 30 25- 20- 15- 10- .. 5- 0 20 40 60 80 100 120 140 Adjusted Gross Income ($1,000s) 0 20 40 60 80 100 120 140 0 Adjusted Gross Income ($1,000s) 20 40 60 80 100 120 140 Adjusted Gross Income ($1,000s) 30 25 20 15 10 5- 0 20 40 60 80 100 Adjusted Gross Income ($1,000s) 120 140 G (b) Use the least squares method to…
As the population ages, there is increasing concern about accident-related injuries to the elderly. An article reported on an experiment in which the maximum lean angle-the farthest a subject is able to lean and still recover in one step-was determined for both a sample of younger females (21-29 years) and a sample of older females (67-81 years). The following observations are consistent with summary data given in the article: YF: 28, 35, 33, 27, 28, 32, 31, 35, 32, 25 OF: 17, 15, 21, 13, 12
Consider the demand for Fresh Detergent in a future sales period when Enterprise Industries' price for Fresh will be x1 = 3.70, the average price of competitors' similar detergents will be x2 = 3.90, and Enterprise Industries' advertising expenditure for Fresh will be x3 = 6.50. A 95 percent prediction interval for this demand is given on the following JMP output: %3D Predicted Lower 95% Upper 95% Mean Demand Upper 95% Indiv Demand StdErr Lower 95% Demand Mean Demand Indiv Demand Indiv Demand 31 8.4106503477 8.3143172822 8.5069834132 0.2393033103 7.9187553487 8.9025453468 E Click here for the Excel Data File; (a) Find and report the 95 percent prediction interval on the output. If Enterprise Industries plans to have in inventory the number of bottles implied by the upper limit of this interval, it can be very confident that it will have enough bottles to meet demand for Fresh in the future sales period. How many bottles is this? If we multiply the number of bottles implied by the lower…
Please solve using SPSS
A number of studies have shown lichens (certain plants composed of an alga and a fungus) to be excellent bio-indicators of air pollution. An article gives the following data (n = 13) on x = NO3- wet deposition (g N/m²) and y = lichen (% dry weight): x 0.05 0.10 0.11 0.12 0.31 0.37 0.42 0.58 0.68 0.68 0.73 0.85 0.92 y 0.53 0.58 0.45 0.54 0.57 0.53 1.03 0.89 0.90 1.02 0.91 1.00 1.66 Predictor Constant no3 depo Estimate 0.39329 0.9286 0.1767 S = 0.1866 R-sq = 71.5% Standard Error 0.09566 t Stat 4.11 5.26 p-value 0.002 0.000 R-sq (adj) = 68.9% (a) What are the least square estimates of B and ẞ₁? (Round your answers to three decimal places.) bo = = (b) What is the margin of error for a 95% CI for ẞ₁? (Round your answer to four decimal places.) Margin of Error = (c) Predict lichen N for an NO3 - deposition value of 0.7. (Round your answer to three decimal places.) % dry weight (d) What is the estimate of σ? (Round your answer to four decimal places.) S = % dry weight

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