Based on the data shown below, calculate the regression line (each value to two decimal places) y = ____ x + ____ x y 3 7.16
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Based on the data shown below, calculate the regression line (each value to two decimal places)
y = ____ x + ____
| x | y |
|---|---|
| 3 | 7.16 |
| 4 | 8.68 |
| 5 | 6.6 |
| 6 | 9.82 |
| 7 | 9.84 |
| 8 | 9.36 |
| 9 | 7.38 |
| 10 | 9.2 |
| 11 | 9.02 |
| 12 | 9.44 |
| 13 | 7.66 |
| 14 | 7.88 |
| 15 | 8.6 |
| 16 | 8.02 |
| 17 | 6.94 |
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
- Special Rounding Instructions For this exercise set, round all regression parameters to three decimal places, but round all other answers to two decimal places unless otherwise indicated. First Down The following table shows the probability P, as a percentage, of a college football team converting on fourth down when not goal to go versus the distance D, in yards, to the first down maker. 28 D = distance, in yards P = probability 1 70 2 60 3 53 4 46 5 41 6 37 7 34 8 32 a.Use exponential regression to model the data. b.Plot the data along with the exponential model. c.What probability does the model give of gaining a first down for fourth down and 10yards to go? Note: the actual probability is 28.Special Rounding Instructions For this exercise set, round all regression parameters to three decimal places, but round all other answers to two decimal places unless otherwise indicated. Cost of Scientific periodicals The table below shows the average cost C, in dollars, of chemistry and physics periodicals tyears after 1980. 29 t=yearssince1980 C=cost,indollars 0 140 5 250 10 410 15 780 20 1300 22 1520 a.Make an exponential model of C as a function of t. b.Plot the data and the exponential model. c.What was the yearly percentage growth rate of the cost of chemistry and physics periodicals? d.If this exponential trend continues, what will be the expected average cost of physics and chemistry periodicals in 2020? Round your answer to the nearest dollar.Cable TV The following table shows the number C. in millions, of basic subscribers to cable TV in the indicated year These data are from the Statistical Abstract of the United States. Year 1975 1980 1985 1990 1995 2000 C 9.8 17.5 35.4 50.5 60.6 60.6 a. Use regression to find a logistic model for these data. b. By what annual percentage would you expect the number of cable subscribers to grow in the absence of limiting factors? c. The estimated number of subscribers in 2005 was 65.3million. What light does this shed on the model you found in part a?
- Based on the data shown below, calculate the regression line (each value to at least two decimal places)y = ____x + ______ x y 1 0.21 2 0.62 3 4.13 4 2.24 5 4.25 6 1.06Based on the data shown below, calculate the regression line (each value to two decimal places)y = x + x y 5 16.8 6 12.4 7 10.3 8 9.9 9 5.6 10 6.2 11 2.9Based on the data shown below, calculate the regression line (each value to two decimal places) Find "( )" y = ( ) x + ( )
- The following regression was estimated using quarterly data for 10 years ??? = −7.453 − 0.0714?? + 0.00315?? − 0.1537?? Se= (13.58) (0.0347) (0.0017) (0.04919) R2= 0.758 ESS = 23.5104 RSS = 14.1867 d=2.04 Where NC = new car sales per 1000 population P = new car price index Y = per capita real disposable income in Rs. i = interest rateBASED ON THIS DATA, what does the r^2 values tell you? and the linear regression line is the information statistically significant?For the simple regression equation (a), conduct an individual significance tests at the 5% significance level to determine if SQFT is a significant predictor of Price. (Check photo for data)
