The lifetime of certain electronic components is assumed to have an exponential distribution. Assuming the average lifespan of these components is 250 hours, ... (a) Find the pdf of the lifespan of these components. (b) Find the median lifespan of these components
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- QUESTION 3 Suppose there are two football teams A and B. In recent matches Team A has a mean of 1 goal per match and Team B has a mean of 2 goals per match. Suppose that the probability of the number of goals scored by a team obeys a Poisson Distribution In the following questions, give the reasoning behind your answers. You can express some answers in terms of logarithms. Q 3(a) What is the probability that A beats B by 1 goal? You can give your answer to 2 decimal places. Q 3(b) If the two teams play each other repeatedly, what is the probability of there being at least 5 matches before A beats B by 1 goal? Q 3(c) In a particular match what is the probability of two goals within the first 20 minutes? Q 3(d) What is the second most probable score line? Q 3(e) In a particular match, over how long a time period would the probability of exactly one goal be 20%?6) The following figure shows that the probability of a plant flowering in 1987 was related to its initial size (as defined by leaf area) in 1984. Also, for a given-size plant, the probability of flowering declines as a function of previous allocation to reproduction (measured as the number of fruits produced during 1984-1986). Based on this figure, approximately how large (leaf area in cm3) would a plant that has produced three fruits over the last three years have to be in order to have an approximately 50% (0.50) probability of flowering? Probability of flowering in 1987 1.0 0.8 0.6 0.4 0.2 00000 ***** AM 100 Question 6 options: 100 cm3 150 cm3 300 cm3 250 cm3 00 .. 200 300 Leaf area in 1984 (cm²) O fruits 1 fruit ▲ 2 fruits 3 fruits 400 500In this example, what is the probability of a person who lives in a single home with a single family with multiple generations getting infected with Covid? Enter the answer to three digits after the decimal place. 
- Suppose that we want to build a model that predicts the group membership of a hurricane, either tropical (0) or non-tropical (1) based on the latitude of formation of the huricane. The response variable is the binary variable Type.new (type of hurricane) and the predictor variable is FirstLat (First Latitude). Using R, we build a model by applying the glm () function. For the logistic regression model, we specify family = "binomial". The data is available at https://userpage.fu-berlin.de/soga/200/2010 data sets hurricanes.xlsx. The R code is #set up filename my.filename 1z|) <2e-16 *** 0.96148 -9.446 0.37283 0.03947 9.447 <2e-16 *** --- *# Signif. codes: 0 '*** 0.001 **' 0.01 '*' 0.05'.' 0.1 '' 1 # (Dispersion parameter for binomial family taken to be 1) Null deviance: 463.11 on 336 degrees of freedom *# Residual deviance: 232.03 on 335 degrees of freedom *# AIC: 236.03 *# Number of Fisher Scoring iterations: 6 What is the interpretation of the p-value of the predictor variable…1.8 Compute and compare the total electricity consumption of Sub-Saharan Africa to the United States in 2012. The population of Sub-Saharan Africa was 926 million, and the United States was 314 million. The per person consumption in the United States in 2012 was 12.96 MWh per year. Consult Fig. 1.11 for the per person consumption in Sub-Saharan Africa.Q2. You collected 500 weeks of data (2500 days total). Based on that you find Tuesday's mean return is 12 bps. Mean return of all days is 2 bps. Stdev across all days is 100 bps. There is no noticeable difference b/w Tuesday stdev vs other weekdays' stdev. Based on q1c find D Q1c. what is the mean log return and stdev of log return over one year period and four year period (assuming 252 trading days per year)? Q1d. based on Q1c what is the probably of losing money (negative log return) or doubling your money (total log return = ln(2)) over 1 year and 4 year period?
- mean(log X)= 3.4, Slogx = 0.136 and k=1.2, using the log Pearson Type III distribution. The magnitude of the 10 yr floods is إختر أحد الخيارات cfs 3657.6 .A O cfs 4570.7 .B cfs 2645.7 .CO cfs 1568.7 .DOPart D. Data from the Statistical Abstract of the United States provides a panel data collected at the state level in 1987 and 1990. These data are used to estimate MODEL 1: The variables used in the analysis are: infmort is number of deaths within the year per 1,000 live births Ipcinc is natural log of per capita income Ipopul is natural log of the population (the population is in thousands) Iphysic is natural log of physicians per 100,000 inhabitants d90 is year dummy for 1990. For questions 1 to 4 you can assume that MLR 1-4 are satisfied. A 1. Use the Stata output below to interpret ß3. Test at a 5% significance level whether the number of physicians per capita has any effect on infant mortality rate. reg infmort 1pcinc 1popul 1physic d90 Source Model Residual Total infmort infmort = Po + B₁lpcinc + B₂lpopul + ß3lphysic + 8₁ d90 + u SS 78.0499129 350.452136 428.502049 df . 19.5124782 4 97 3.61290862 Coef. Std. Err. MS 101 4.24259454 1pcinc -4.693354 1.638132 1popul - .0551426…QUESTION 3 Suppose there are two football teams A and B. In recent matches Team A has a mean of 1 goal per match and Team B has a mean of 2 goals per match. Suppose that the probability of the number of goals scored by a team obeys a Poisson Distribution In the following questions, give the reasoning behind your answers. You can express some answers in terms of logarithms. Q 3(d) What is the most probable score line? Q 3(e) In a particular match, over how long a time period would the probability of no goals be 20%?
- Consider 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.Consider the logit regression log(odds(QualExam) = ßo + B, • ParEduc + B, • Awards. where QualExam is a binary variable that indicates passing the exam if equal to 1, and failing the exam if 0, ParEduc indicates the parents' education level, and Awards is a binary variable that indicates having experience of obtaining award(s) if equal to 1, and not having experience if 0. Given the parents' average education level unchanged, the odds ratio is expected to be _ for an individual with awards to pass the exam comparing to those without awards. For an individual without awards and the parents' education level of 4, the estimated probability of passing the exam is approximately_. ParEduc Awards Intercept -10.53 2.98 0.48 O A. 0.48; 80%. O B. 1.616; 80%. O C. 1.616; 4%. O D. 0.48; 4%.Would you include ros in a final model explaining CEO compensation in terms of firm performance?
