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## Info3010, Week 14 notes

by: Rebecca Evans

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# Info3010, Week 14 notes Info3010

Marketplace > Tulane University > Business > Info3010 > Info3010 Week 14 notes
Rebecca Evans
Tulane
GPA 4.0

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How to interpret linear regression models and use the results.
COURSE
PROF.
Srinivas Krishnamoorthy
TYPE
Class Notes
PAGES
2
WORDS
KARMA
25 ?

## 0

This 2 page Class Notes was uploaded by Rebecca Evans on Wednesday April 13, 2016. The Class Notes belongs to Info3010 at Tulane University taught by Srinivas Krishnamoorthy in Spring 2016. Since its upload, it has received 17 views. For similar materials see Business Modeling in Business at Tulane University.

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Date Created: 04/13/16
4.11 Broadway Box Office and Linear Regression  To download: o Fileoptionsadd-insmanage excel add-insadd in analysis tool-pack  To use regression o Datadata analysisregression o Input y-range: select column title and entire column (select a few cellsshift+control+down arrow to select entire column automatically) o Dependent variable: weekly gross \$ (input y-range) o Independent variable: previous week’s gross income (input x-range) 4.13 Broadway Box Office and Regression  Output: rd o Y-intercept=\$17,956 (coefficietnts, intercepts under 3 tarde) o Slope=0.96 (coefficients, previous week’s gross under 3 table) o Gross \$=\$17,956 + (0.96)previous week  P-value has to be less than 0.05 for the relationship to be valid o Find p-value: 3 table: p-value (column) and previous week’s gross \$ (row)  Error term: part unexplained by model o Gross \$=\$17,956 + (0.96)previous week + random error term Making predictions  Point prediction o Prediction is single point or number o Suppose previous week \$=\$200,000 o Gross \$=\$17,956 + (0.96)(\$200,000)= \$210,252 o But single number is not that accurateprefer to have a range  Interval prediction  95% interval prediction o Start with a point prediction \$210,252 o Endpoints: point estimator +/- (2)standard error o Standard error (1 table, “regression statistics”) ----------------------------------------- \$210,252----------------------------------------------------- o Endpoints \$210,252 +/- (2)(67,652) o Endpoints=\$345,557 and \$74,947 o Standard distribution: capture 95% of data within 2 standard distributions awayuse 2 standard errors to find endpoints  Standard error similar to standard deviation o Spread out range because of the industry is high risk/unpredictable Exam  Don’t need to know how to create these tables  Need to be able to interpret table and outputs  Friday-watch videos online  Monday-regression and course wrap up  Wednesday, Friday, Monday-review Assignment 2 Most points off-question #1  Bayesian table Survey Positive negative Total Actual Successful 500(1-x) 500x 500 Unsuccessfu False positive=(0.3) 500-150= 500 l (500)= 350 150 Total 500(1-x)+150 1000  P(actually successful if survey says positive)=0.7  False positive= (500)(1-x)/ ((500(1-x)) +150)

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