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SCENARIO 17-6 the Neural Network Output Below Was Obtained for Predicting the Predicting

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SCENARIO 17-6
The neural network output below was obtained for predicting the weekend box office revenue of a newly released movie (in thousands of dollars)based on data collected in different cities on the expenditure (at $25,$30,$35,$40,$45,$50,$55,$60 $65 or $70 thousands)spent on TV advertising and the number of times (10,15,20,25,30 or 35)a day the advertisement appear on TV.
SCENARIO 17-6 The neural network output below was obtained for predicting the weekend box office revenue of a newly released movie (in thousands of dollars)based on data collected in different cities on the expenditure (at $25,$30,$35,$40,$45,$50,$55,$60 $65 or $70 thousands)spent on TV advertising and the number of times (10,15,20,25,30 or 35)a day the advertisement appear on TV.    -Referring to Scenario 17-6,what is the r-square of model for the validating data?
-Referring to Scenario 17-6,what is the r-square of model for the validating data?


Definitions:

Type II Error

A statistical error occurring when the null hypothesis is not rejected when it actually is false.

Type II Error

The error that occurs when a statistical test fails to reject a false null hypothesis, mistakenly indicating that a difference or effect does not exist.

Two-Tailed

Refers to a hypothesis test where the area of interest spans both tails of the distribution, allowing for testing of differences in both directions.

One-Tailed

A hypothesis test where the area of interest is only on one side of the distribution, testing for a direction-specific outcome.

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