Concept explainers
Two components operate in parallel in a device, so the device fails when and only when both components fail. The lifetimes,
The cost of operating the device is
Compute E(Z).
Want to see the full answer?
Check out a sample textbook solutionChapter 5 Solutions
Pearson eText for Probability and Statistical Inference -- Instant Access (Pearson+)
- The following Table summarizes the main estimation results for the below model: C- Bo + B,R + Balet E.where (C) denotes total household Consumption in SL, (R) is the national Incorme, and (1) denotes the Taxes collected from the private sector. The time span goes from 1974, 1st quarter, to 2010, 4th quarter and all the variables are expressed in million Rupees. Dependent variable C Constant R. Coefficient Sd. Eror t-statisties 128 40 3.2 0.90 0.48 0.67 6.0 32 0.15 0.15 R squared Residual Std. 1.35 Deviation Given the information in above table and the null that the Given the information in above table and the null that the Taxes collected from the private sector (B2) is not equal to zero, O a. There is not enough information to test this hypothesis. O b. The test statistic can be computed and the null is rejected in favor of the alternative hypothesis with a 5% significance. O . None cof the these O d. The test statistic can be computed and the null is not rejected in favor of the…arrow_forwardObtain the regression equation of Y on X for the following distribution. ƒ (x, y) = 7ix* exp (-y/1 +x); x, y 20.arrow_forwardConsider the following estimated model, where the dependent variable is the log of the hourly wage: log(wage) = 0.417 - 0.238female + 0.17educ + 0.0232 exper - 0.00058exper? +0.0295tenure – 0.00059tenure? female 1 if the person is female, and 0 if the person is male educ = level of education, in years exper = level of expertise, in years tenure = duration of tenure, in years Given that the above regression model has 313 observations, then its degrees of freedom is equal to For the same levels of education, expertise, and tenure, women earn exactly % less compared to men, holding other factors fixed.arrow_forward
- The moment generating function can be used to find the mean and variance of the normal distribution. Use derivatives of Mx(t) to verify that E(X) = µ and V(X) = 0².arrow_forwardThe output of a solar panel (photovoltaic) system depends on its size. A manufacturer states that the average daily production of its 1.5 kW system is 6.6 kilowatt hours (kWh) for Perth conditions. A consumer group monitored this 1.5 kW system in 20 different Perth homes and measured the average daily production by the systems in these homes over a one month period during October. The data is provided here. kWh 6.2, 5.8, 5.9, 6.1, 6.4, 6.3, 6.9, 5.5, 7.4, 6.7, 6.3, 6.2, 7.1, 6.8, 5.9, 5.4, 7.2, 6.7, 5.8, 6.9 1. Analyse the consumer group’s data to test if the manufacturer’s claim of an average of 6.6 kWh per day is reasonable. State appropriate hypotheses, assumptions and decision rule at α = 0.10. What conclusions would you report to the consumer group? (Hint: You will need to find Descriptive Statistics first.) 2. If 48 homes in the central Australian city of Alice Springs had this system installed and similar data was collected, in order to assess whether average daily production in…arrow_forwardThe risk of a person developing heart disease is correlated with their BMI (or body mass index), which is calculated by dividing their body mass by their height (high BMIS typically mean the person is overweight). Heart disease is also related to a person's level of activity. Suppose a person's BMI is x and their physical activity is y (measured, for example, in minutes of exercise each day). Let h be a heart disease risk index (high values of h mean high risk of heart disease, low values of h mean a low risk of heart disease). h depends on x and y, that is, h3h(x,y). A simple linear model that only takes into account the effects of BMI and activity is (a) Would you expect a > 0 or a < 0? What about b? You would expect a 7o and b 0. (b) To fit the values of a and b, consider the following data. A patient with BMI of 15, and who does 50 min of activity each day, has risk index h = 150. A patient with BMI of 30, and who does 30 min of activity each day, has risk index h = 405. Use these…arrow_forward
- The value of the correlation r = (x,y) for the information would be: n = 8, Sum(x) = 609, Sum(y) = 504, Sum (x)^2 = 47995, Sum (y)^2 = 32954, and Sum (xy) = 395650 Choose answer from the following: a. 0.855 b.0.174arrow_forward(c) Derive the mean square error (mse) of ê. (d) Find the method of moments estimator (mme) of 0. Denote it by 0.arrow_forwardAn investor has found that company1 have an expected return on E(X) = 4% and variance for the return equal V(X) = 0.49. Company 2 has E(Y) = 6% and variance V(Y) = 0.64. The correlation between the companies return is ρ(X,Y) = 0.3. The investor wants to invest p (0<p<1) in company1 and (1-p) in company2. The combined investment have a return: R = pX + (1-p)Y. Let p=0.4 such that R= 0.4X +0.6Y. Find the Expectation and variance of R. how are these results in comparison with X and Y separatley?arrow_forward
- What is the Dirichlet ruler function?arrow_forwardA professor in a university polled a dozen colleagues about the number of professional meetings they attended in the past five years (x) and the number of papers they submitted to refereed journals (y) during the same period. The summary data are given as follows: n = 12, x = 4, y = 12, Σx?232, 2 x;yi = 318. i=1 i=1 1. Find the values of SSXX and SSxy. and SSy 2. Find a simple linear regression model between x and y by finding out the estimates of intercept and slope. Bo = and B = %3Darrow_forwardThe 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?arrow_forward
- Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage LearningAlgebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:CengageTrigonometry (MindTap Course List)TrigonometryISBN:9781337278461Author:Ron LarsonPublisher:Cengage Learning