Linear Regression Use linear regression to find the equation for the linear function that best fits this data. Round both numbers to two decimal places. Write your final answer in a form of an equation y = mx + b y 1 68 2 3 4 5 6 92 109 136 150 170

Given the data points listed below, use linear regression to find the expression y = %3D mx + b. List the slope of the best-fit line in the box below (round to one digit past the decimal point). y 2 2 3 15 5 14 8 55 |13 68 15 121

Let ŷ represent the profit (in thousands of dollars) for a certain company xx years after 1965. A statistician calculates a linear model ŷ = 0.38xx + 15Use the model to estimate the profit in 1973.  Your answer should be in dollars, not thousands of dollars.Profit =$

Use the data shown in the graph to write a quadratic regression equation. Then predict the box office revenue in 2013. Let x represent the number of years since 2000. Millions of dollars 32- 189 31+ 30- Box office revenue 28.9 29.4 28.7 30.8 29- 28- 27- 2004 2005 2006 2007 2008 2009 Year

The value of your investment real estate, which is valued today at $231,000 , is projectedto appreciate to $270,000 in six years. Find the linear equation expressing the $ value V(t)of that real estate as a linear function of time t in years

The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995. 220- 210 200 190 180 170 160 150 Year 0 130- 120- 110- 100- 90 801 6 12 15 Let S(t) be the retails sales in billions of dollars in t years since 1995. A linear model for the data is F(t) = 9.44t + 84.182. Retail Sales 85.851 108.426 141.781 169.256 202.297 222.266 3 6 9 12 15 Use the above scatter plot to decide whether the linear model fits the data well. The function is a good model for the data. The function is not a good model for the data Estimate the retails sales in the U. S. in 2015. billions of dollars.

The data show the bug chirps per minute at different temperatures. Find the regression​ equation, letting the first variable be the independent​ (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted​ value? Chirps in 1 min  1118  796  1161  918  1103  1219 Temperature (F)   82    72.2   92.2   73   87.5   94.4

Use linear regression to find the equation for the linear function that best fits this data. Click Read Button For online regression calculator.  Round both numbers to two decimal places. Write your final answer in a form of an equation   y=mx+by=mx+b  x 1 2 3 4 5 6 y 74 90 109 123 143 155