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Regression and policy analysis

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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
0.037
5.16 *
Teaching Hospital or Non-
teaching hospital
(1=teaching, 0= others)
0.032
0.22
Occupancy Rate
-0.032
3.46*
Number of Hospital Beds
0.007
1.48
Region (1= central, 0=others)
-0.035
7.68*
R-square = 0.61
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 variableâ??s
coefficient and t-statistic 8%
(b) Interpret the R-square term 2%

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Interpretation of regression data, independent variables and t-statistics

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The t-statistic is a measure of statistical significance. It tells us how certain we can be that this is not a random correlation. We can never be completely sure, so we generally specify a high rate of statistic significance, such as 95 or 98%. If it were at 95%, for example, it would tell us that there is less than a 5% probability of getting a value as high as this by chance alone.

The Coefficient tells us how much, and in which ...

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