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=25.0+4.85X.
| Predictor | Coef | SE Coef | T | P |
|---|---|---|---|---|
| Constant | 25.028 | 5.406 | 4.63 | 0.000 |
| X | 4.853 | 0.7309 | 6.64 | 0.000 |
Intercept β0: Enter your answer; Intercept
Slope β1: Enter your answer; Slope
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- What is interpolation when using a linear model?Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300Assume a regression model is y= -4.72+3.27. give a forecast of y when x= 25.62
- Use the regression line to make the appropriate prediction. A random sample of records of electricity usage of homes in the month of July gives the amount of electricity used and size (in square feet) of 135 homes. A regression was done to predict the amount of electricity used (in kilowatt-hours) (y) from size (x). The residuals plot indicated that a linear model is appropriate. The model is y = 0.2x + 1271. How much electricity would you predict would be used in a house that is 2471 square feet? 1765.2 kilowatt-hours 6000.00 kilowatt-hours 3742.2 kilowatt-hours 494.2 kilowatt-hours 776.8 kilowatt-hoursA regression line calculated as y= 9.7-3.2x. The slope of this line is -3.2 TRUE OR FALSEUse the computer output to estimate the intercept β0 and the slope β1.The regression equation is Y=816-4.32X. Predictor Coef SE Coef T P Constant 816.348 88.73 9.20 0.000 X -4.324 1.418 -3.05 0.006 Intercept β0: Enter your answer; InterceptSlope β1: Enter your answer; Slope
- 2. A high school track & field coach wanted to assess the relationship between an athletes height and how far they can jump in the long jump event (both in inches). They collect data on each athletes height and how far they can jump. Let the height in inches of the athlete be the explanatory variable (X) and the distance in inches of the jump be the response (Y). The scatterplot of the data based on 32 athletes is as follows: distance 88 86 84 82 80 78 00 O o 70 Scatter Plot 72 height 00 000 00 00 8 74 8 O ¥75 76 一念 78Use the regression equation to predict the value of y= -2.8. Assume that the variable x and y have a significantThe number of students in a school chorus has increased since the school first opened 6 years ago. The linear regression equation describing the change is y = 14x + 17, where a represents the year and y represents the number of students. a. Complete the table to determine the residuals for the numberr of students. Then create a residual graph with the X's on the x axis and residuals on the y-axis. Predicted Number of Residual Value Year Number of Students Students 22 26 40 59 78 4 83 Residual Plot 6 -4 3 2 -2 -1 -1 916 esc DII F4 FS F7 FB @ %23 2$ 1 2 3. 4. 7 8. Q W E R T Y tab S D F G caps lock Z C V N shift B A
- Use the given data to find the equation of the regression line. Round the final values to three places, if necessary. (1, 6), (3, 4), (5, 2) O = -2.79 + 0.897x O ý = 1.0 + 1.0x O ý = 7.0 - 1.0x O ý = -3.79 + 0.801xFind the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 450 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 233 270 Crash Fatality Rate 16 15.9 Find the equation of the regression line. y=16.728+(-0.0031)x (Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.) The best predicted crash fatality rate for a year in which there are 450 metric tons of lemon imports is fatalities per 100,000 population. (Round to one decimal place as needed.) ew an example Get more help. W S k X H and # 3 SO F3 E 26 D 358 492 535 15.6 15.3 15 C $ 4 Q FA R LI F 25 V % S 9 FS T G 6 B 746 MacBook Air Y H & 7 N F7 U J * 00 8 DII FB I M ( 9 X. K FO O < مو I O F10 Clear all qqqqqqqqı P L I Л. ... I d FIT { + […A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.223 b=22.907 r2=0.600625 r=-0.775 Use this to predict the number of sit ups a person who watches 5 hours of TV can do, and please round your answer to a whole number.
