Statistics that summarize personal health care expenditures by state for the yea
ID: 3056473 • Letter: S
Question
Statistics that summarize personal health care expenditures by state for the years 1966 through 1982 have been examined in an attempt to understand issues related to rising health care costs. Suppore that you are interested in focusing on the relationship between expense per admission into a community hospital and average length of stay in the facility. The data set hospital contains information for each state in the united states (including the District of Columbia) for the year 1982[7] (Appendix B, Table B.26). The measures of mean expense per admisssion are saved under the variable name expadm; the correspinding average lengths of stay are under los.
Use SAS.
a. Generate numerical summary statistics for the variables expense per admission and length of stay in the hospital. What are the means and medians of each variable? What are their minimum and maximum values?
b. construct a 2-way scatter plot of expense per admission versus length of stay. What does the scatter plot suggest about the nature of the relationship between the variables>
c. Using expense per admission as the response and length of stay as the explanatory variable, compute the least-squares regression line. Interpret the estimated slope and y-intercept of this line in words.
d. Construct a 95% confidence interval for B, the true slope of the population regression line. What does this interval tell you about the linear relationship between expense per admission and length of stay in the hospital?
e. What is the coefficient of determination for the least-squares line? How is R(squared) related to the Pearson correlation coefficient r?
f. Construct a plot of the residuals versus the fitted values of expense per admission. In what 3 ways does the residual plot help you to evaluate the fit of the model to the observed data?
It should solved by SAS
TABLE B.26 Data set hospital; variobles state, expadn, los, Connecticut 3328 78 1695 2810 7.7 14317 4105 8.9 15696 Massachusetts New Hampshire 2487 7.1 13542 Rhode Island Vermont Delaware District of 3380 85 14947 2478 8.2 13432 2957 8.2 15717 Columbia Maryland New York New Jersey Pennsylvania Illinois Indiana Michigan 4612 8.7 18700 3210 8.3 15213 2712 84 15573 3607 9.7 16657 3194 8.5 15256 3351 8.0 16872 2592 7.8 13946 3351 8.0 16635 3007 8.1 15492 2724 8.3 14951 2361 8.0 13579 2600 7.8 14107 2730 9.4 14503 2915 80 14950 2448 84 13584 2277 86 13559 2059 8.7 12508 2174 72 12834 Wisconsin lowa Minnesota North Dakota South Dakota AlabamaExplanation / Answer
SOlutionA:
import the dataset into sas as ds1
Run th e below procedure:
proc univariate data=ds1;
var expadm los ;
run;
solutionb:
proc sgplot data=ds1;
scatter x=los y=expadm;
run;
solutionc:
expense per admission as the response ----dependent varaible
and length of stay as the explanatory variable,------independent variable.
proc reg data=ds1;
model expadm=los/lackfit;
plot expadm*los;
run;
solutiond:
proc reg is used to fit linear regression models by least squares estimation
proc reg data=ds1;
model expadm=los/clb;
run;