MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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- Data is collected on the relationship between time spent playing video games and time spent with family. The data is shown in the table and the line of best fit for the data is ŷ =−0.27x+57.5. Assume the line of best fit is significant and there is a strong linear relationship between the variables Video Games(minutes) Time with Family(minutes) 30 50 60 40 90 35 120 25 According to the line of best fit, the predicted number of minutes spent with family for someone who spent 95 minutes playing video games is 31.85. Is it reasonable to use this line of best fit to make the above prediction? Select the correct answer below: The estimate, a predicted time of 31.85 minutes, is unreliable but reasonable. The estimate, a predicted time of 31.85 minutes, is both unreliable and unreasonable. The estimate, a predicted time of 31.85 minutes, is both reliable and reasonable. The estimate, a predicted time of 31.85 minutes, is reliable but unreasonable.arrow_forwardA data set whose original x values ranged from 120 through 351 was used to generate a regression equation of ŷ=0.06x + 14.2. Use the regression equation to predict the value of y when x=110.arrow_forwardThe graph of a function passes through the point (50, 3.6), and y varies inversely as x. Find the value of y when x is 75. A) Calculate the value of k = xy. SAMSUNG ロarrow_forward
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- I need help with finding constants and coefficients for the equation of y hat. Please make sure to round as required in the attachmentarrow_forwardA value of r close to plus or minus 1 indicates that there is a strong linear relationship between the variables true or false?arrow_forwardThe costs of various sailboats of varying lengths are xx, length in feetyy, thousands of dollars......The line of best fit for the data in this table (no data shown) is y=3.28x−22.59y=3.28x-22.59. Approximate the cost of a sailboat (to the nearest thousand) that is 30 ftftlong. $ thousandarrow_forward
- This question has do with linear regression.If I consider attendance in a class versus final grade in the class can you explain where there is a positive and when there is a negative relationship between them.arrow_forwardIf the equation of the regression line for hours a spent cycling in the summer and hours y spent working in the summer is ŷ = - 0.7x + 42 , then as the number of cycling hours increases, the number of work hours tends to decrease. true O falsearrow_forwardSometimes we have data that can be paired together, such as height and weight of an individual. When two variables are measured and paired together, we have what we call paired data. When we have paired data, we can plot the results using a scatterplot. This will give us a visual to determine if there is a relationship between the variables of interest. For two variable relationships, we can often report the data as ordered pairs in (x, y) format. Our x-variable in this case is known as the explanatory variable, and the y-variable is known as the response variable. We use values of x to predict y. If there appears to be a linear relationship between the two variables, we can create a least squares regression line. This is a line that “best” fits the dataset we have. The result will be a linear equation and we can use this equation to predict future values. For simple linear regression (ordered pairs with only two variables), the general form of a regression line follows:�̂=β0+β1�,…arrow_forward
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