You test the effect of the gender and age on survival of patients receiving kidney. You use the proportional hazard model with the indicator variable Z1 = 1 for male patient and Z2 = 1 for adult patient. The resulting parameter estimates are b1 = 0.25, b2 = –0.45. The variance-covariance matrix for b1 and b, is 0.35 0.10 0.10 0.20

You test the effect of the gender and age on survival of patients receiving kidney. You use the proportional hazard model with the indicator variable Z1 = 1 for male patient and Z2 = 1 for adult patient. The resulting parameter estimates are b1 = 0.25, b2 = –0.45. The variance-covariance matrix for b1 and b, is 0.35 0.10 0.10 0.20

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.1: Measures Of Center

Problem 9PPS

See similar textbooks

Similar questions

2. Given the following sets of information, find the linear least squares regression and the correlation coefficient.
Suppose that the index model for two Canadian stocks HD and ML is estimated with the following results: RHD =-0.03+2.10RM+eHD R-squared =0.7 RML =0.06+1.60RM+eML R-squared =0.6 σM =0.15 where M is S&P/TSX Comp Index and RX is the excess return of stock X. What is the covariance and the correlation coefficient between HD and ML?
In the packaging department of a large aircraft parts distributor, a fairly reliable estimate of packaging and processing costs can be determined by knowing the weight of an order. Thus, the weight is a cost driver that accounts for a sizable fraction of the packaging and processing costs at this company. Data for the past 10 orders are given as follows. Solve, a. Estimate the b0 and b1 coefficients, and determine the linear regression equation to fit these data. b. What is the correlation coefficient (R)? c. If an order weighs 250 lb, how much should it cost to package and process it?
A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: City Price ($) Sales River City 1.30 100 Hudson 1.60 90 Ellsworth 1.80 90 Prescott 2.00 40 Rock Elm 2.40 38 Stillwater 2.90 32 What is the coefficient of correlation for these data? -0.7839 0.8854 0.7839 -0.8854
During a 5-week period in 2007, the stock of an insurance company and the stock of a small tech company showed the following weekly percentage changes.Company Weekly Price Change (%)Insurance Stock 0.3 1.8 0 0. -1.5Tech Stock 0.3 -0.1 1.1 3.2 0.8 Find the variance of the weekly price changes of each. (Round your answers to four decimal places.) insurance stock= tech stock=
The following matrix shows the bivariate correlations for houses with garages. Baths Beds Sqft Age Price Baths 1 Beds 0.591 1 Sqft 0.696 0.626 1 Age -0.427 -0.133 -0.069 1 Price 0.643 0.374 0.767 -0.099 1 Baths: # of bathrooms in the house Beds: # of bedrooms in the house Sqft: # of square feet in the house Age: age of the house in years Price: selling price of house Answer the following: a) Do older houses with garages sell for lower or higher prices than newer houses with garages on average? Are older houses with garages smaller or larger than newer houses with garages on average? b) Is the correlation between baths and age weaker or stronger than correlation between beds and price? c) Is the correlation between age and sqft weaker or stronger than the correlation between age and price?
In the packaging department of a large aircraft parts distributor, a fairly reliable estimate of packaging and processing costs can be determined by knowing the weight of an order. Thus, the weight is a cost driver that accounts for a sizable fraction of the packaging and processing costs at this company. Data for the past 10 orders are given as follows: a. Estimate the b0 and b1 coefficients, and determine the linear regression equation to fit these data. b. What is the correlation coefficient (R)? c. If an order weighs 205 lb, how much should it cost to package and process it? Packaging and Processing Cost ($), y Weight (Pounds), x 99 240 111 275 86 210 85 185 121 315 114 300 111 285 100 270 109 275 85 200
If a sample of 25 pairs of data yields a correlation coefficient, r, of 0.390 and the scatterplot displays a linear trend, can you use the regression equation to make predictions, assuming your x-values are within the domain of the data set? Choose your answer from the multiple choice answers below A.) Yes, because rcrit = 0.396 and the regression coefficient, r, is less than this value. B.) Yes, because rcrit = 0.381 and the regression coefficient, r, is greater than this value. C.) No, because rcrit = 0.381 and the regression coefficient, r, is greater than this value. D.) No, because rcrit = 0.396 and the regression coefficient, r, is less than this value.
In a typical multiple linear regression model where x1 and x2 are non-random regressors, the expected value of the response variable y given x1 and x2 is denoted by E(y | 2,, X2). Build a multiple linear regression model for E (y | *,, *2) such that the value of E(y | x1, X2) may change as the value of x2 changes but the change in the value of E(y | X1, X2) may differ in the value of x1 . How can such a potential difference be tested and estimated statistically?
A researcher interested in the correlation between family size X annual income Y and parental education level Z produces the following correlation matrix x. y. z x +1.00. +0.32. +0.56 y. +0.32. +1.00. +0.88 z. +0.56. +0.88. +1.00 What is the correlation between annual income and parental education level?