1) Find the regression equation and r value Drop Height, y (m) Square of Mean Fall time, t^2 (s^2) 0.100 0.0188 0.300 0.0576 0.500 0.0980 1.000 0.198 1.500 0.305 2.500 0.508
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1) Find the regression equation and r value
|
Drop Height, y (m) |
Square of Mean Fall time, t^2 (s^2) |
|
0.100 |
0.0188 |
|
0.300 |
0.0576 |
|
0.500 |
0.0980 |
|
1.000 |
0.198 |
|
1.500 |
0.305 |
|
2.500 |
0.508 |
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- Can the average rate of change of a function be constant?Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.778b=0.143 (d) If the life expectancy is increased by 5 years in a certain country, how much will the happiness index change? Round to two decimal places.(e) Use the regression line to predict the happiness index of a country with a life expectancy of 94 years. Round to two decimal places.
- 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=ax+b a= -0.921 b= 39.616 r^= 0.483025 r= -0.695 Use this to predict the number of situps a person who watches 11.5 hours of TV can do (to one decimal place)A regression line has a intercept value of 190 and slope value of 11.55. What is the predicted value (the y-value) in the 1st period (the x-value is 1)?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:ˆy=bx+ay^=bx+ab=−1.217b=-1.217a=39.762a=39.762R2=0.695556R2=0.695556a) Use this to predict the number of situps a person who watches 13 hours of TV can do (to 3 decimal places) b) What is the value of the correlation coefficient (to 3 decimal places) ?
- A regression was run to determine if there is a relationship between hours of study per week (xx) and the final exam scores (yy). The results of the regression were: ˆy=y^=5.06x+x+24.49r2=r2=0.619369 r=r=0.787 Use this to predict the final exam score of a student who studies 12 hours per week, and please round your answer to a whole number.The linear regression equation for predicting systolic blood pressure from age is: ˆyy^ = 47 + 2.2*x Find the residual for a person who is 36 years of age with a systolic blood pressure of 128.3 (round your answer to one decimal place)When the level of investment expenditures of non-manufacturing firms in the US (denoted as Y), from 1960 to 1979, is regressed on the GNP (denoted as X1), and the consumer price index (denoted as X2), the following results are obtained: Y^t = 31.75 + 0.08 X1t - 0.58 X2t R2= 0.98 (6.08) (3.08) d = 0.77 Note: the numbers in parentheses represent t-ratios and d= Durbin-Watson statistic. Which type of problem is existed in the model? Why is it a problem? How can we detect this problem? How could it be corrected?
- approximate using linearization and use a calculator to compute the percentage error. (64.1)^ 1/3A regression line for a set of data is calculated and found to be y^=85+12x. Use this to predict a value of y when x= 0.Given the power regression model y = 20x^1.6, which is the linear regression model after transforming to a log-log graph? A. Y = 1.6x + 1.30 B. Y = 1.3X + 1.60 D. Y = 0.2X + 0.20 C. Y = 0.2X + 1.30
