The answer is 1.75
because the cost on the y axis goes by fourths
Independent variable is the predictor variable which is the height and dependent variable is the response variable which is weight in this scenario.
The square of correlation coefficient gives the coefficient of determination. It is denoted by R² (R squared).
We are given:
R = 0.75
So,
R² = 0.75²
R² = 0.5625
R² = 56.25 %
The coefficient of determination tells how much of the trend of dependent data can be explained by the independent data using the linear regression model. So in the given case, Height can explain 56.25% of the trend in the weight.
Step-by-step explanation:
We find the equation of the solid blue line:
The line decreases by 1 unit for every 3 units across.
=> Slope of line = -1/3.
Also the y-intercept is 1.
=> Line equation: y = -1/3 x + 1.
We see that the graph below this line is shaded.
Therefore all y-values below or on the line are represented by the graph.
=> y <= -1/3 x + 1.
The answer is y <= -1/3 x + 1.
Answer:
the answer is c because it can be either greatly increased or decreased
