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What is the Prediction Interval (1 decimal)? Lower value:  Upper value:  The Confidence Interval will be __________ (wider or narrower) than the Prediction Interval. Which interval is the appropriate one to use when estimating the average starting salary for students with a 6.8 GPA?  Confidence Interval Prediction Interval

What is the Prediction Interval (1 decimal)? Lower value:  Upper value:  The Confidence Interval will be __________ (wider or narrower) than the Prediction Interval. Which interval is the appropriate one to use when estimating the average starting salary for students with a 6.8 GPA?  Confidence Interval Prediction Interval

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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What is the Prediction Interval (1 decimal)?

Lower value: 

Upper value: 

The Confidence Interval will be __________ (wider or narrower) than the Prediction Interval.

Which interval is the appropriate one to use when estimating the average starting salary for students with a 6.8 GPA? 
Confidence Interval
Prediction Interval
Student GPA starting salaries 4.5 48094 5.8 42400 6.1 50987 5.5 40598 4.7 53500 4.1 36184 3.9 32115 6.5 51250 5.6 45155 4.8 37108 3.5 34540 4.05 39250 starting salaries 4.5 41500 7.5 60230 90000 7.4 58750 80000 6.2 52900 70000 y = 6971.4x + 10599 R = 0.8196 7.8 58700 60000 4.5 40135 50000 8.8 70214 starting salaries 40000 8.5 73065 -Linear (starting salaries ) 8.7 68952 30000 3.5 38786 20000 2.5 39102 10000 7.5 71020 8.1 75401 2. 6. 10 8.3 81203 เก่ เก่ -00 00 oc
Transcribed Image Text:Student GPA starting salaries 4.5 48094 5.8 42400 6.1 50987 5.5 40598 4.7 53500 4.1 36184 3.9 32115 6.5 51250 5.6 45155 4.8 37108 3.5 34540 4.05 39250 starting salaries 4.5 41500 7.5 60230 90000 7.4 58750 80000 6.2 52900 70000 y = 6971.4x + 10599 R = 0.8196 7.8 58700 60000 4.5 40135 50000 8.8 70214 starting salaries 40000 8.5 73065 -Linear (starting salaries ) 8.7 68952 30000 3.5 38786 20000 2.5 39102 10000 7.5 71020 8.1 75401 2. 6. 10 8.3 81203 เก่ เก่ -00 00 oc
OFF A A E S a S1 - AC - GPA data solution AutoSave Insert Draw Page Layout Formulas Data Review View Q Tell me O Comments Home 2 Share Σ. “江"。. Calibri (Body) v A A = = ab wrap Text v A Insert v 11 General EX Delete v 4 v A v Sensitivity Paste E Merge & Center v $ v % 9 .00 .00 →0 Conditional Format Formatting as Table Styles Cell Sort & Filter Find & Select BIUV += += Ideas H Format v Open recovered workbooks? Your recent changes were saved. Do you want to continue working where you left off? Yes No E12 fx A D E G H K L N P S V X Y 1 Student GPA starting salaries 2 4.5 48094 5.8 42400 4 6.1 50987 5.5 40598 6. 4.7 53500 7 4.1 36184 8 3.9 32115 9 6.5 51250 10 5.6 45155 11 4.8 37108 12 3.5 34540 13 4.05 39250 starting salaries 14 4.5 41500 15 7.5 60230 90000 16 7.4 58750 80000 17 6.2 52900 70000 y = 6971.4x + 10599 R = 0.8196 18 7.8 58700 60000 19 4.5 40135 50000 20 8.8 70214 • starting salaries 40000 21 8.5 73065 -Linear (starting salaries ) 22 8.7 68952 30000 23 3.5 38786 20000 24 2.5 39102 10000 25 7.5 71020 26 8.1 75401 2 4 6 8 10 27 8.3 81203 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 data regression Sheet2 Sheet3 囲 100%
Transcribed Image Text:OFF A A E S a S1 - AC - GPA data solution AutoSave Insert Draw Page Layout Formulas Data Review View Q Tell me O Comments Home 2 Share Σ. “江"。. Calibri (Body) v A A = = ab wrap Text v A Insert v 11 General EX Delete v 4 v A v Sensitivity Paste E Merge & Center v $ v % 9 .00 .00 →0 Conditional Format Formatting as Table Styles Cell Sort & Filter Find & Select BIUV += += Ideas H Format v Open recovered workbooks? Your recent changes were saved. Do you want to continue working where you left off? Yes No E12 fx A D E G H K L N P S V X Y 1 Student GPA starting salaries 2 4.5 48094 5.8 42400 4 6.1 50987 5.5 40598 6. 4.7 53500 7 4.1 36184 8 3.9 32115 9 6.5 51250 10 5.6 45155 11 4.8 37108 12 3.5 34540 13 4.05 39250 starting salaries 14 4.5 41500 15 7.5 60230 90000 16 7.4 58750 80000 17 6.2 52900 70000 y = 6971.4x + 10599 R = 0.8196 18 7.8 58700 60000 19 4.5 40135 50000 20 8.8 70214 • starting salaries 40000 21 8.5 73065 -Linear (starting salaries ) 22 8.7 68952 30000 23 3.5 38786 20000 24 2.5 39102 10000 25 7.5 71020 26 8.1 75401 2 4 6 8 10 27 8.3 81203 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 data regression Sheet2 Sheet3 囲 100%
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