2. Assume that you are a policy analyst. Your staff has collected cross-sectional data on the determinants of average length of stay in various hospitals. A staff member hands you the following table or regression results, assuming that you know how to interpret it. Table. Regression Results for the Impact of Various Factors on Average Hospital Length of Stay t-Statistics Independent Variable Intercept Term Coefficient 0.038 3.56 * Teaching Hospital or Non-teaching Hospital (1=teaching, 0= others) -0.1542 2.95* Number of Hospital Beds -0.327 3.89* Occupancy Rate -0.276 1.58 Number of physicians 0.185 3.44* 2.67* Region (1= central, 0=others) R-square = 0.398 0.165 %3D An asterisk indicates that the coefficient is statistically significant in a two-tailed test at the 95% confidence level. (a) In no more than two sentences each, interpret each independent variable's coefficient and t-statistic (Including, coefficient, significance and if the conclusion reliable or not) (b) Interpret the R-square term

2. Assume that you are a policy analyst. Your staff has collected cross-sectional data on the determinants of average length of stay in various hospitals. A staff member hands you the following table or regression results, assuming that you know how to interpret it. Table. Regression Results for the Impact of Various Factors on Average Hospital Length of Stay t-Statistics Independent Variable Intercept Term Coefficient 0.038 3.56 * Teaching Hospital or Non-teaching Hospital (1=teaching, 0= others) -0.1542 2.95* Number of Hospital Beds -0.327 3.89* Occupancy Rate -0.276 1.58 Number of physicians 0.185 3.44* 2.67* Region (1= central, 0=others) R-square = 0.398 0.165 %3D An asterisk indicates that the coefficient is statistically significant in a two-tailed test at the 95% confidence level. (a) In no more than two sentences each, interpret each independent variable's coefficient and t-statistic (Including, coefficient, significance and if the conclusion reliable or not) (b) Interpret the R-square term

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

2. Assume that you are a policy analyst. Your staff has collected cross-sectional data on the
determinants of average length of stay in various hospitals. A staff member hands you the
following table or regression results, assuming that you know how to interpret it.
Table. Regression Results for the Impact of Various Factors on Average Hospital Length of Stay
Independent Variable
Coefficient
t-Statistics
Intercept Term
0.038
3.56 *
Teaching Hospital or Non-teaching
Hospital (1=teaching, 0= others)
-0.1542
2.95*
Number of Hospital Beds
-0.327
3.89*
Occupancy Rate
-0.276
1.58
Number of physicians
0.185
3.44*
k.67*
Region (1= central, 0=others)
R-square = 0.398
0.165
An asterisk indicates that the coefficient is statistically significant in a two-tailed test at the
95% confidence level.
(a) In no more than two sentences each, interpret each independent variable's coefficient
and t-statistic (Including, coefficient, significance and if the conclusion reliable or not)
(b) Interpret the R-square term

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