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- 2. Suppose that in a certain chemical process the reaction time y (hour) is related to the temperature x (° F) in the chamber in which the reaction takes place according to the simple linear regression model with equation y= 5 - 0.01x and the standard deviation o=0.075. a. What is the expected reaction time when temperature is 250° F? b. Suppose that five observations are made independently on reaction time, each one for a temperature of 250° F. What is the probability that all five times are between 2.4 and 2.6 hours?X X zy Section 5.4- QNT/275T: Statistics x + 598163/chapter/5/section/4 for Decision Making home > nce between two population means 4.1: Hypothesis test for the difference between two population means. Jump to level 1 A clinical researcher performs a clinical trial on 14 patients to determine whether a drug treatment has an effect on serum glucose. The sample mean glucose of the patients before and after the treatment are summarized in the following table. The sample standard deviation of the differences was 8. Before treatment What is the test statistic? Ex: 0.123 Check What type of hypothesis test should be performed? Select Select Left-tailed z-test Paired t-test Two-tailed z-test Unpaired t-test Next After treatment 75 Sample mean glucose (mg/dL) What is the number of degrees of freedom? Ex: 25 Does sufficient evidence exist to support the claim that the drug treatment has an effect on serum glucose at the a = 0.05 significance level? Select 81 MESA 81101 2 hp 3 ISuppose you are to estimate a simple regression for the following population model: Y=B₁ + B₁X + µl From a population of over thousands of observations, a small number of samples were randomly selected. The following is some of the information from the randomly selected sample.
- The first independent variable (Xt2) will be a cubed value of the rate of return on individual companies. Is the inclusion of this variable consistent with the assumptions of the simple linear regression model? Explain your answer b. What is the additional assumption for this time-series model that does not apply to a cross-sectional analysis? c. If you suspected that your dependent variable Y was not stationary, explain the three unit root processes that you could test for. d. What does the letter "t" represent in the model?Please help on my assignment. ThanksThe US government is interested in understanding what predicts death rates. They have a set of data that includes the number of deaths in each state, the number of deaths resulting from vehicle accidents (VEHICLE), the number of people dying from diabetes (DIABETES), the number of deaths related to the flu (FLU) and the number of homicide deaths (HOMICIDE). Your run a regression to predict deaths and get the following output: At α = .10, which variable(s) is/are significant predictors of deaths?
- We are interested in estimating the following model log(wage) = Bo + Bieduc + Bzexper + u where • wage=hourly wage, in US dollars; • educ=number of years of education; • exper=number of years of work experience. The variable ctuit is the change in college tuition facing students from age 17 to age 18 and is used as an IV for educ. We run the first stage regression for educ and get the following output: Source s df MS Number of obs 1,230 F (2, 1227) 550.19 Model 3220.84426 2 1610.42213 Prob > F 0.0000 Residual 3591.43541 1,227 2.92700523 0.4728 R-squared Adj R-squared 0.4719 Total 6812.27967 1,229 5.54294522 Root MSE 1.7108 educ Coef. Std. Err. t P>|t| [95% Conf. Interval] ctuit -.1859575 .0608175 -3.06 0.002 -.3052752 -.0666398 exper -.521161 .0157156 -33.16 0.000 -.5519933 -.4903286 _cons 18.63905 .1757961 106.03 0.000 18.29415 18.98394 Is the assumption of instrument relevance satisfied? Why yes, or why not?The following table gives the regression results of consumption behaviour between female and male. Consumption (C), in RM Model 1 Model 2 Constant 0.7515 0.6587 (0.024) (0.037) Y 0.8603 0.5442 (0.0301) (0.2881) Gen 0.2001 (0.0004) Y*Gen 0.3105 (0.0076) Adjusted R 0.78 0.78 No. of Observations 47 47 Note: Y=income (RM) Gen= Gender ( It is equal to 1 if person is female; 0 is for male) Figures in the parentheses are p- values a) Identify which are the qualitative, quantitative and interaction variable. Refer to Model 1: b) Write the regression equations for female and male. Draw the regression lines for female and male on the same diagram. What can you c) say? d) Interpret all the estimated slope coefficients. e) Conduct an appropriate test to determine whether variable gender is statistically significant at 5%. Should this variable be dropped from this regression model.Here's a table with average monthly price of a stock from Jan 2021-July 2021. Month Price Jan 29000 Feb 27000 Mar 31000 Apr 30000 May 32000 June 28000 July 29000 Using a 3-period weighted moving average with weights (wt, wt-1, W-2) = (0.6, 0.2, 0.2), the predicted price August is Using an exponential smoothing model with = 0.4, and with the initial predicted price for Jan the same as the observed price for January, the predicted price for August is % Now, let's suppose that we finally observe that the price for August is 30000. The absolute percent error (APE) of your prediction for August is using the weighted moving average method and % using the exponential smoothing model. (Note: Round your answer to the nearest 2 decimal places. For your APE answer for example let's say you get 0.06786 from Excel, then you should type-in 6.79 as your answer here since it is represented as percentage. Do not enter any symbols other than integers and decimal.)
- Please solve 12.7 and dont use any programme like minitab.In an M/MA queueing system, the arrival rate is 5 customers per hour and the service rate is 9 customers per hour. If the service process is automated (resulting in no variation in service times but the same service rate), what will be the resulting performance measurements? (Round your answers to 3 decimal places.) 2.do fast
