The population growth of a state since 2000 in millions of people is represented by a linear model. Using the trend line, y=0.83x+30 , predict the population, y , in the year 2030. Let x=30 because the year 2030 is 30 years after the year 2000.(1 point)
Using the linear model y=0.83x+30 and substituting x=30 for the year 2030, we can find the predicted population:
y = 0.83(30) + 30
y = 24.9 + 30
y = 54.9
Therefore, the population in the year 2030 is predicted to be approximately 54.9 million people.
Your teacher surveyed the class to determine the number of hours that each student spent on social media. Your teacher created a table and scatterplot graph that displayed the number of hours, x , and the average final grade percentage, y , based on the hours. Using the equation of the trend line of the data, y=–7.2x+98.9 , predict the average final grade percentage, to the nearest whole number, if a student spent 10 hours on social media.
Using the equation of the trend line provided, y = -7.2x + 98.9, and plugging in x = 10, we can calculate the predicted average final grade percentage:
y = -7.2(10) + 98.9
y = -72 + 98.9
y = 26.9
Rounding to the nearest whole number, the predicted average final grade percentage if a student spent 10 hours on social media is 27%.
You are snow skiing down a mountain that is represented by the linear model y=–30x+6,000 , where y is the number of feet after x seconds. Predict your elevation level in feet if you ski 60 seconds.
Using the linear model y = -30x + 6000 and substituting x = 60 for 60 seconds, we can find the predicted elevation level:
y = -30(60) + 6000
y = -1800 + 6000
y = 4200
Therefore, your elevation level in feet after skiing for 60 seconds is predicted to be 4200 feet.