was nominated (1976-2015)
Based on the output (including the graph) below, about how many nominations are needed to have a 20% chance of winning Best Picture?
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Logistic Regression - winners
Dependent variable: 1=won 0= loss
Factors: number of categories nominated
Estimated Regression Model (Maximum Likelihood)
|
Standard |
Estimated |
||
|
Parameter |
Estimate |
Error |
Odds Ratio |
|
CONSTANT |
-5.17048 |
0.737865 |
|
|
number of categories nominated |
0.462202 |
0.0835516 |
1.58757 |
Analysis of Deviance
|
Source |
Deviance |
Df |
P-Value |
|
Model |
38.9351 |
1 |
0.0000 |
|
Residual |
172.834 |
226 |
0.9965 |
|
Total (corr.) |
211.769 |
227 |
Percentage of deviance explained by model = 18.3857
Adjusted percentage = 16.4968
Likelihood Ratio Tests
|
Factor |
Chi-Square |
Df |
P-Value |
|
number of categories nominated |
38.9351 |
1 |
0.0000 |

log (p/(1-p)) = -5.17048 + 0.4622 * x
here p = 0.2
hence
log(0.2/0.8) = -5.17048 + 0.4622 * x
solving x = 8.18
about 8 nomination
Please rate
was nominated (1976-2015) Based on the output (including the graph) below, about how many nominations are...
Consider the multiple linear regression given below. How many predictor variables currently look "significant" in the model? Multiple Regression Standard T Parameter Estimate Error Statistic P-Value CONSTANT 33113.2 9684.08 3.41934 0.0009 Latitude -269.803 191.056 -1.41216 0.1610 Longitude 29.9439 65.7703 0.455279 0.6499 AthleticRevenue 0.0001411 0.0000350024 4.03115 0.0001 Endowment 0.00173455 0.00106854 1.62329 0.1076 Analysis of Variance Source Sum of Squares Df Mean Square F-Ratio P-Value Model 3.52982E9 4 882,455,000 0.0000 Residual 9.8797E9 101 97,818,800 Total (Corr.) 1.34095E10 105 R-squared = 26.3232 percent
Fit a logistic regression model with perio as the outcome and
exposures sep0, sep1, smoke and oralhyg.
The result is following:
Provide an interpretation of the estimated parameters smoke and
oralhyg - what are the implications for someone who smokes but who
also has good oral hygiene
habits?
I know this question is a bit tricky, so if you get some idea, I
will regard it as helpful!
Variable Description id unique identifier perio 1 = periodontitis, 0 = no...
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