1. Find the regression equation. 2. Estimate the mental ability of an individual from the same population who has an SES rating 9.0
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- Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $130 million. Use a significance level of α=0.05. A. The regression equation is Y= (Round to one decimal place as needed.) B. The best predicted gross for a movie with a $130 million budget is $ million. (Round to one decimal place as needed.)2. Develop an estimated regression equation that can be used to predict Winnings ($) given the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), and the number of top ten (Top 10) finishes. Test for individual significance and discuss your findings and conclusions. Driver Points Poles Wins Top 5 Top 10 Winnings ($) Tony Stewart 2403 1 5 9 19 6,529,870 Carl Edwards 2403 3 1 19 26 8,485,990 Kevin Harvick 2345 0 4 9 19 6,197,140 Matt Kenseth 2330 3 3 12 20 6,183,580 Brad Keselowski 2319 1 3 10 14 5,087,740 Jimmie Johnson 2304 0 2 14 21 6,296,360 Dale Earnhardt Jr. 2290 1 0 4 12 4,163,690 Jeff Gordon 2287 1 3 13 18 5,912,830 Denny Hamlin 2284 0 1 5 14 5,401,190 Ryan Newman 2284 3 1 9 17 5,303,020 Kurt Busch 2262 3 2 8 16 5,936,470 Kyle Busch 2246 1 4 14 18 6,161,020 Clint Bowyer 1047 0 1 4 16 5,633,950 Kasey Kahne 1041 2 1 8 15 4,775,160 A.J. Allmendinger 1013 0 0 1 10 4,825,560 Greg Biffle 997 3 0 3 10…Nine pairs of data yield a regression equation of y=0.93x + 19.4, with r= 0.967 and an average y value of 64.70. What is best predicted value for y when x =65? Is it 79.85, 25.74, 89.61, 57.82, 70.55, 96.70, 19.40, or 64.70?
- Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.3 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) 7.8 175 7.3 9.5 274 7.4 156 9.9 294 9.2 183 256 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... The regression equation is y =+x. (Round to one decimal place as needed.)Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.1 per 10 million people? Internet Users Per 100 Nobel Laureates80.3 5.679.6 24.277.3 8.644.6 0.183 6.138.3 0.190.1 25.189.1 7.680.1 8.983.3 12.753.2 1.976.6 12.756.8 3.379.5 1.591.5 11.493.7 25.465.1 3.157.8 1.967.9 1.794.3 31.785.3 31.387.7 1977.7 10.86, 5. Kathy painted a picture and posted it on a social media site. The table shows the number of people who responded that they liked the picture since Kathy posted it. Time Since Picture Was Posted 5. 7. (days) Number of Likes 11 21 38 Write the regression equation that best models the data. a. y = 0.96(1. 55)* b. y = 2.07(1. 38)* c. y = 0.536x – 0.857x + 1.81 d. y = 1.38x´ + 0.30x + 0. 43
- Suppose a new location opens in an area with a population of 144,000, an average income of$36,000, an average age of 27, and $2,000 spent on advertising in the previous month.a. Use your chosen regression to predict Gross Sales for the month at the new location. (I picked population)b. Suppose actual Gross Sales for the month were $420,624. Does this make sense,given your model and predicted value?12. Using your chosen regression model,a. Identify the slope and explain what it means, in the context of the model.b. Identify the initial value or y-intercept and explain what it means, in the context ofthe model.1. School administrators believe their freshman applications are influenced by two variables: tuition and the size of the applicant pool of eligible high school seniors in the state. The following data for an 8-year period show the tuition rates (per semester) and the sizes of the applicant pool for each year: Tuition in pesos Applicants Pool Applicants 27000 76,200 11,060 37500 78,050 10,900 41250 67,420 8,670 42000 70,390 9.050 46500 62,550 7,400 48750 59,230 7,100 52500 57,900 6,300 57900 60,080 6,100The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $6 million. Is the result close to the actual number of viewers, 8.9 million? Use a significance level of 0.05. Salary (millions of $) Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. 98 3.5 3 7 13 12 13 10 2 6.8 6.3 10.2 8.5 4.4 1.8 2.7 What is the regression equation? y=+x (Round to three decimal places as needed.) What is the best predicted number of viewers for a television star with a salary of $6 million? The best predicted number of viewers for a television star with a salary of $6 million is million. (Round to one decimal place as needed.) Is the result close to the actual number of viewers, 8.9 million? O A. The result is very close to the actual number of viewers of 8.9 million. O B. The…
- The accompanying table shows a portion of data that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City. Click here for the Excel Data File Taxes Size 21,987 2,403 17,353 2,451 29,238 2,866 a. Estimate the sample regression equation that enables us to predict property Taxes on the basis of the size of the home. (Round your answers to 2 decimal places.) Taxes = + Size. b. Interpret the slope coefficient. O As Property Taxes increase by 1 dollar, the size of the house increases by 6.71 ft. O As Size increases by 1 square foot, the property taxes are predicted to increase by $6.71. c. Predict the property Taxes for a 1,400-square-foot home. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.) TaxesFind the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.5 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 7.6 7.4 9.8 8.8 9.3 7.3 Weight (kg) 142 163 256 188 231 156 The regression equation is y= + x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 2.5 cm is kg? (Round to one decimal place as needed.) Can the prediction be correct? What is wrong with predicting the weight in this case? A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data. B. The prediction cannot be correct because a negative weight does not make sense and because there is…2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?