Use the computer output to estimate the intercept β0 and the slope β1.
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Use the computer output to estimate the intercept β0 and the slope β1.
The regression equation is Y=26.4+4.10X.
| Predictor | Coef | SE Coef | T | P |
|---|---|---|---|---|
| Constant | 26.432 | 5.709 | 4.63 | 0.000 |
| X | 4.103 | 0.6179 | 6.64 | 0.000 |
Intercept β0:
Slope β1:
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- Use the computer output to estimate the intercept β0 and the slope β1.The regression equation is Y=26.0+3.74X. Predictor Coef SE Coef T P Constant 26.023 5.621 4.63 0.000 X 3.738 0.5630 6.64 0.000 Intercept β0: Slope β1:A regression analysis was performed to determine if there is a relationship between hours of TV watched per day () and number of sit ups a person can do (y). The results of the regression were: y=ax+b a3D-0.838 b=28.783 es 72-0.784996 r=-0.886 rences borations Use this to predict the number of sit ups a person who watches 1 hours of TV can do, and please round your answer to a whole number. gle Drive ce 365 Submit Question adent Course aluations ere to search Chp ins prt sc delete f12 f9 f10 fa f5 f6 +1 f4 backspa & $4 8. 6 3 O E R T II 5The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
- The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 57 inches. Is the result close to the actual weight of 476 pounds? Use a significance level of 0.05. 44 Chest size (inches) Weight (pounds) 58 48 51 58 60 425 266 347 453 282 408 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... What is the regression equation? y=+x (Round to one decimal place as needed.) Activate Windows View an example Get more help- Help me solve this O Type here to search hp delete insert prt sc f12 f1o fg 1 f7 f6 f5 f3 米 IOI f1 esc hom backspace 6. L. 4 U E R tab F G J. A caps lock pause 00 9, %24 3. %23Interpret the intercept and the coefficients of D1 and D2 in the regression above.Use the computer output to estimate the intercept β0 and the slope β1.The regression equation is Y=825-3.12X. Predictor Coef SE Coef T P Constant 825.405 89.72 9.20 0.000 X -3.119 1.023 -3.05 0.006 Intercept β0: Slope β1: Click if you would like to Show Work for this question: Open Show Work
- Using the given equation for the regression line shown, determine the amount of time required to completely burn the candle. [2C] A Burning Candle 35.0 30.0 25.0 y = -0.2x + 30 20.0 15.0 10.0 5.0 0.0 20 40 60 80 100 Time (min) Height of Candle (cm)The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 924 1150 840 1166 1087 930 Temperature (°F) 77.5 84.6 74.1 91 79.6 79.7 What is the regression equation? What is the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute? What is wrong with this predicted value? Choose the correct answer below. A. It is unrealistically high. The value 3000 is far outside of the range of observed values. B. The first variable should have been the dependent variable. C. It is only an approximation. An unrounded value would be considered accurate. D. Nothing is wrong with this value. It can be…The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 63 inches. Is the result close to the actual weight of 532 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 58 414 50 312 65 59 59 499 48 g 450 456 260 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y = x (Round to one decimal place as needed.) - Critical Values of the Pearson Correlation Coefficient r Critical Values of the Pearson Correlation Coefficient r α = 0.05 α=0.01 NOTE: To test Ho: p=0 4 0.950 0.990 against H₁: p0, reject Ho 5 0.878 0.959 if the absolute value of ris 6 0.811 0.917 7 0.754 0.875 greater than the critical value in the table. 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17…
- A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=a+bx b=-0.993 a=29.135 r2=0.463761 r=-0.681 Use this to predict the number of situps a person who watches 6 hours of TV can do. Round to one decimal place.Compute the least-squares regression equation for the given data set. Round the slope and yFintercept to at least four decimal places. 4 y 7. 3. Send data to Excel Regression line equation: y =|
