Select all the charts that violate the conditions for linear regression. (a) (b) (c)

The following data is the number of tickets sold and the jackpot value for the Mega Millions lottery. The jackpot value is in millions of dollars and the number of tickets sold is in millions. Jackpot value 334 127 300 227 202 180 164 145 255 Number of tickets sold 54 16 41 27 23 18 18 16 26 r= 0.947 tickets sold -10.87 +0.17 (jackpot value) Which is the independent variable and which is the dependent variable? X= independent variable = Y= dependent variable Interpret ². Interpret the slope. Predict the number of tickets sold when the jackpot value is 500 million dollars. Would you feel comfortable using the model for this value? Why or why not.

a and b please

(d) Write out the regression equation. (Use 2 decimal places.) x1 = + x2 + x3 + x4 If x2 (production costs) and x4 (book sales) were held fixed but x3 (promotional costs) were increased by 0.7 million dollars, what would you expect for the corresponding change in x1 (box office receipts)? (Use 2 decimal places.)(e) Test each coefficient in the regression equation to determine if it is zero or not zero. Use level of significance 5%. (Use 2 decimal places for t and 3 decimal places for the P-value.)   t P-value β2     β3     β4     (f) Find a 90% confidence interval for each coefficient. (Use 2 decimal places.)   lower limit upper limit β2     β3     β4

How is the Polynomial Regression model different from the Simple Linear Regression and Multiple Linear Regression models? Select an answer: a. The independent variables are categorical instead of numerical. b. There are multiple dependent variables instead of just one. c. The independent variable is raised to a higher power (squared, cubed, etc.). d. The dependent variable is raised to a higher power (squared, cubed, etc.).

Altitudes in thousand of feet and outside temperatures in degrees F. altitude: 3|10|14|22|28|31|33 temp: 57|37|24|-5|-30|-41|-54 does a strong linear between altitude and temp exist? If so how and  A. Find a regression ax+b for temp as a function of altitude b. If the altitude is 18,500ft, what's the expected temp then? c. If the temp is at a freezing mark, what's the expected altitude?

The table shows a country's average fuel consumption for "light duty" vehicles (passenger cars and small trucks) for several years. Let x be the number of years since 1985, so that x = 5 stands for 1990 and so forth. Year Fuel Economy (mpg) 1990 16.9 1995 17.7 2000 18.3 (a) Find the linear regression model for these data. What does the slope in the regression model represent? 2005 18.9 (b) Use the linear regression model to predict the country's average fuel economy for light duty vehicles in the year 2035. 2010 19.6 (a) Find the linear regression model for these data. Choose the correct answer below. (Use integers or decimals for any numbers in the equation. Round to the nearest hundredth as needed.)