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If you used this regression to predict Tesla sales, how many more years will it take to double total sales (# sold) beyond the 2022 sales level? (Show your calculations.) Do you think this is a good prediction? Explain why or why not. The blow regression is the effect of time on In(Total Sales) Regression Statistics Multiple R R Square Adjusted R Sq 0.94711655 Standard Erro 0.69874288 Observations ANOVA Regression Residual Total 0.97513791 0.95089394 Intercept Time df 15 $$ MS Significance F 1 122.90658 122.90658 251.733114 6.8937E-10 13 6.3471409 0.48824161 14 129.253721 Coefficients itandard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 4.84930862 0.37966765 12.7725095 9.8536E-09 4.02908654 5.66953071 4.02908654 5.66953071 0.66253458 0.04175787 15.8660995 6.8937E-10 0.57232218 0.75274698 0.57232218 0.75274698

If you used this regression to predict Tesla sales, how many more years will it take to double total sales (# sold) beyond the 2022 sales level? (Show your calculations.) Do you think this is a good prediction? Explain why or why not. The blow regression is the effect of time on In(Total Sales) Regression Statistics Multiple R R Square Adjusted R Sq 0.94711655 Standard Erro 0.69874288 Observations ANOVA Regression Residual Total 0.97513791 0.95089394 Intercept Time df 15 $$ MS Significance F 1 122.90658 122.90658 251.733114 6.8937E-10 13 6.3471409 0.48824161 14 129.253721 Coefficients itandard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 4.84930862 0.37966765 12.7725095 9.8536E-09 4.02908654 5.66953071 4.02908654 5.66953071 0.66253458 0.04175787 15.8660995 6.8937E-10 0.57232218 0.75274698 0.57232218 0.75274698

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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AutoSave OFF Home Insert Get Data (Power Query) Q15 A 1 SUMMARY OUTPUT 2 3 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 14 15 ANOVA 16 17 Regression 18 Residual 19 Total 20 21 22 Intercept 23 Time B Regression Statistics Ready Draw df 1 2 ✓ C ... Sheet2 15 Page Layout Formulas V Refresh All C =8-0 Queries & Connections Properties Edit Links Open recovered workbooks? Your recent changes were saved. Do you want to continue working where you left off? fx Sheet1 D Data Review View E Accessibility: Investigate Organization F SS MS F Significance F 1 122.90658 122.90658 251.733114 6.8937E-10 13 6.3471409 0.48824161 14 129.253721 Stocks G Automate H > ↓ I A Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 4.84930862 0.37966765 12.7725095 9.8536E-09 4.02908654 5.66953071 4.02908654 5.66953071 0.66253458 0.04175787 15.8660995 6.8937E-10 0.57232218 0.75274698 0.57232218 0.75274698 X Tesla sales ✓ Tell me Sort Filter J Clear Reapply Advanced K L Text to Columns M Flash Fill Remove Duplicates N 40 00 O Data Validation ✓ Consolidate P What-If Analysis Q 4 If you used this regression to predict Tesla sales, how many more years will it take to double total sales (# sold) beyond the 2022 sales level? (Show your calculations.) Do you think this is a good prediction? Explain why or why not. The blow regression is the effect of time on In(Total Sales) 5 6 7 8 9 Multiple R 0.97513791 10 R Square 0.95089394 11 Adjusted R Sq 0.94711655 12 Standard Erro 0.69874288 13 Observations R 888 Group ✓ E Ungroup v Subtotal B S 1.1.9 Comments I T Analysis Tools Share Data Analysis Yes U No + 100% V
Transcribed Image Text:AutoSave OFF Home Insert Get Data (Power Query) Q15 A 1 SUMMARY OUTPUT 2 3 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 14 15 ANOVA 16 17 Regression 18 Residual 19 Total 20 21 22 Intercept 23 Time B Regression Statistics Ready Draw df 1 2 ✓ C ... Sheet2 15 Page Layout Formulas V Refresh All C =8-0 Queries & Connections Properties Edit Links Open recovered workbooks? Your recent changes were saved. Do you want to continue working where you left off? fx Sheet1 D Data Review View E Accessibility: Investigate Organization F SS MS F Significance F 1 122.90658 122.90658 251.733114 6.8937E-10 13 6.3471409 0.48824161 14 129.253721 Stocks G Automate H > ↓ I A Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 4.84930862 0.37966765 12.7725095 9.8536E-09 4.02908654 5.66953071 4.02908654 5.66953071 0.66253458 0.04175787 15.8660995 6.8937E-10 0.57232218 0.75274698 0.57232218 0.75274698 X Tesla sales ✓ Tell me Sort Filter J Clear Reapply Advanced K L Text to Columns M Flash Fill Remove Duplicates N 40 00 O Data Validation ✓ Consolidate P What-If Analysis Q 4 If you used this regression to predict Tesla sales, how many more years will it take to double total sales (# sold) beyond the 2022 sales level? (Show your calculations.) Do you think this is a good prediction? Explain why or why not. The blow regression is the effect of time on In(Total Sales) 5 6 7 8 9 Multiple R 0.97513791 10 R Square 0.95089394 11 Adjusted R Sq 0.94711655 12 Standard Erro 0.69874288 13 Observations R 888 Group ✓ E Ungroup v Subtotal B S 1.1.9 Comments I T Analysis Tools Share Data Analysis Yes U No + 100% V
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