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Levart [38]
2 years ago
8

The data below shows the points scored and minutes played by six basketball players during the 2004-2005 season. The least squar

es regression line for the data is y=.79x+1544
Mathematics
1 answer:
k0ka [10]2 years ago
5 0

We assume data and prediction as question is incomplete

Answer and Step-by-step explanation:

Least squares regression line equations are used to model the relationship that exists between two variables, dependent and independent variables. The equation has the form y=a+bx where y is the dependent variable and x is independent variable, a is a constant and is the y intercept and b is the slope of the line. This relationship is then used to predict future outcomes.

Given that data for 2004-2005 for the basketball players are :

James- 20 points

John- 30 points

Chris- 50 points

Dave-15 points

Donaldson- 32 points

Richard -40 points

We predict the scores/points for James (for example) for the following year using the equation of the regression line y=0.79x+1544

We substitute his points x=20 I'm the equation:

Y=0.79*20+1544

=1599.8

The predicted value is 1599.8

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Answer:

Container A is filling more quickly

Step-by-step explanation:

<em>Let us explain the linear relation</em>

The linear equation is y = m x + b, where

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  • b is the y-intercept which means the initial amount of y (at x = 0)

<em>If a line represents the amount of water over time, then it represents the rate of filling of the water</em>

∵ There are two containers A and B that have the same size

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∴ The slopes of the lines represent the rat of water in the tanks

→ That means the greater slope represents the greater rate

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→ The line represents container A is steeper more than the line

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City A grows by 5% every year. In 2021, it has a population of 145,201. What will the population be in 2037?
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2 years ago
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