Classify the following as a linear relationship, exponential relationship, or neither. Explain your reasoning and how you found your answer mathematically! x y 1 2.1 2 1.2 3 0.3 4 -0.6 5 -1.5 6 -2.4

Does the table describe a linear or exponential fuction and do they change by equal differences or equal factors. X -2 -1 0 1 2 Y. 5 3 1 -1 -3

Which function has a greater rate of change, y = 2x or y = -4x (Answer only with 8th Grade knowledge)

The accompanying data represent the yearly amount of solar power installed (in megawatts) in a particular area from 2000 through 2008. The trend forecasting equations below were found, where X is the number of years after 2000. Complete parts (a) through (d) below. = -10.711 +28.9000X₁ ₁ = 22.70 +0.259X; +3.5801X? Click the icon to view the data table. a. Compute the standard error of the estimate (Syx) for each model. Linear Quadratic Syx 22.431 8.032 (Round to three decimal places as needed.) b. Compute the MAD for each model. Linear Quadratic MAD 64.222 66.873 (Round to three decimal places as needed.) c. On the basis of (a) and (b) and the principle of parsimony, which forecasting model would you select? The model with the smallest values of Syx and MAD should be used, which is the quadratic model.

Interpret the unstandardized coefficient for highest years of schooling. E.g., Is the relationship positive or negative? How does a one-unit change in schooling (i.e. an increase in one-year of education) influence Y?  Interpret the constant (i.e. the intercept) in the equation? What does it indicate? Calculate the average number of hours watched for someone with 12 years of education.

A car initially sold for $23,999. Its class life is 12 years, and the car depreciates by $750 each year. Express this as a linear function. Find the salvage value. Then, find the value after six years.

The table compares x, the number of minutes of television Sam watched each day, to y, the number of minutes she spent exercising. The function y =-0.78x %3D + 95 models the data in the table. Recreational Time Minutes of Exercising, y 60 45 Minutes of Television Viewing, x 45 65 120 22 80 80 25

Gordon borrowed $420 from Lyn and agreed to pay her back $24 every month. Write a formula (linear model) showing the amount of money Gordon still owes at any time. Clearly define your variables.

George works a job where he receives an hourly wage plus a bonus for being on time every day. The table below shows his wages for four weeks in which he was on time every day.   Hours Worked 38 34 40 37 Wages Earned ($) 609 547 640 593.50           Write an equation to represent the relationship

The following data was collected to explore how the number of square feet in a house, the number of bedrooms, and the age of the house affect the selling price of the house. The dependent variable is the selling price of the house, the first independent variable (x1�1) is the square footage, the second independent variable (x2�2) is the number of bedrooms, and the third independent variable (x3�3) is the age of the house. Effects on Selling Price of Houses Square Feet Number of Bedrooms Age Selling Price 11191119 33 33 100900100900 13081308 33 44 119800119800 14521452 33 66 189800189800 16931693 33 66 190500190500 20052005 33 66 196900196900 22102210 33 99 216600216600 23012301 44 99 250900250900 23452345 44 1010 267800267800 28532853 55 1313 270000270000 Copy Data Step 1 of 2 :   Find the p-value for the regression equation that fits the given data. Round your answer to four decimal places