D: 0.45 is a positive slope. The dependent variable y increases as the independent variable x increases.
A positive correlation means that as the independent variable increases, the dependent variable also increases. In this case, the independent variable is the number of miles traveled (x) and the dependent variable is the cost of a plane ticket (y). The positive slope of 0.45 indicates that as the number of miles traveled increases, the cost of the ticket also increases.
Ted researched the price of airline tickets and discovered a correlation between the price of a ticket and the number of miles traveled. After recording his data on a scatter plot, he determined the equation for the line of best fit is y = 300 + 0.45x. How can you tell from the equation that the correlation between the cost of a plane ticket and the number of miles traveled is positive? What does a positive correlation tell you about the dependent and independent variables?
A: A positive correlation cannot be determined from examining an equation.
B: 300 is a positive y-intercept. The dependent and independent variables must be positive.
C: 300 is a positive x-intercept. The dependent and independent variables must be positive.
D: 0.45 is a positive slope. The dependent variable y increases as the independent variable x increases.
7 answers
Rob is saving money for a down payment on a house. He opens a savings account at his local bank and deposits $1000. He models his savings plan with the equation y = 400x + 1000 based on his current income and monthly savings rate. What is the meaning of the y-intercept in the equation?
The y-intercept in the equation y = 400x + 1000 is 1000. In this context, the y-intercept represents the initial amount of money Rob deposited into his savings account. It can be interpreted as the starting point or the amount he had saved before he began saving according to his current income and monthly savings rate. Therefore, the y-intercept of 1000 represents the initial $1000 that Rob deposited into his savings account.
A small company did an analysis of their pay scale versus years of experience and found that the line of best fit was y = 2035.6x + 36,000. What does the 2035.6 mean in context of the problem?
In the context of the problem, the value 2035.6 represents the slope of the line of best fit.
More specifically, this slope indicates the average increase in salary (represented by y) for each additional year of experience (represented by x). Therefore, for every additional year of experience, the average salary of an employee at the small company increases by $2035.6.
More specifically, this slope indicates the average increase in salary (represented by y) for each additional year of experience (represented by x). Therefore, for every additional year of experience, the average salary of an employee at the small company increases by $2035.6.
Ashley calculates her salary (base and commission) for the year "y" using the model y = 0.2x + 25,000; where x represents her total sales for the year. What is the meaning of the y-intercept in the model?
In the given model y = 0.2x + 25,000, the y-intercept is 25,000.
In the context of the problem, the y-intercept represents Ashley's base salary. It indicates the amount of money she earns regardless of her total sales (represented by x). Therefore, even if Ashley does not make any sales in a year, she will still receive a base salary of $25,000.
In the context of the problem, the y-intercept represents Ashley's base salary. It indicates the amount of money she earns regardless of her total sales (represented by x). Therefore, even if Ashley does not make any sales in a year, she will still receive a base salary of $25,000.