Choose all statements that are correct. There is a positive correlation between x and y There is a weak correlation between x and y There might be a negative correlation between x and y There is a strong linear correlation between x and y If x increases, we expect y to increase also The regression equation 'fits' the data pretty well

Choose all statements that are correct. There is a positive correlation between x and y There is a weak correlation between x and y There might be a negative correlation between x and y There is a strong linear correlation between x and y If x increases, we expect y to increase also The regression equation 'fits' the data pretty well

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The equation of a regression line, unlike the correlation, depends on the units we use to measure the explanatory and response variables. Here is the data on percent body fat and preferred amount of salt. Preferred amountof salt x 0.2 0.3 0.4 0.5 0.6 0.8 1.1 Percent body fat y 20 31 22 29 39 22 30 In calculating the preferred amount of salt, the weight of the salt was in milligrams. (a) Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in milligrams. (Round your answers to one decimal place.) ŷ = ? + ? x (b) A mad scientist decides to measure weight in tenths of milligrams. The same data in these units are as follows. Preferred amountof salt x 2 3 4 5 6 8 11 Percent body fat y 20 31 22 29 39 22 30 Find the equation of the regression line for predicting percent body fat from preferred amount of salt when weight is in tenths of milligrams. (Round your intercept to one decimal place and your slope…
6, 5. Kathy painted a picture and posted it on a social media site. The table shows the number of people who responded that they liked the picture since Kathy posted it. Time Since Picture Was Posted 5. 7. (days) Number of Likes 11 21 38 Write the regression equation that best models the data. a. y = 0.96(1. 55)* b. y = 2.07(1. 38)* c. y = 0.536x – 0.857x + 1.81 d. y = 1.38x´ + 0.30x + 0. 43
Thank you for your response! that was helpful. I thought the research scenario was imlying a positive correlation, such that as height increases, weight increases. Thus, i thought correlation would be most appropriate. Especially considering that we do not have a data set to predict from. I did not know we can do a linear regression without having a known variable to predict from. Just clarifying, would it still not be appropriate to do a correlation?
Please tell it is true or false
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
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Needed to be solved part 36 and 37 correclty in 30 minutes and get the thumbs up. Please show neat and clean work
Many small companies buy advertising without considering its effect. The marketing manager is trying to make the case that "you have to spend money to make money." Spending on billboard advertise ments, in the manager's opinion, has a direct effect on sales. These are records for 7 months in 1000s: Monthly expenditure on 21 25 billboards 16 42 34 10 19 Monthly sales Develop a regression estimating equation. If the monthly expenditure on billboards is 20,000/- what is the monthly sale generated 34 14 48 32 26 29 20
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?
When you are deciding which variables to include as predictors in a multiple regression equation, what are some conditions that you must consider first?
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In a simple regression analysis (where y is a dependent and x an independent variable), if the slope is positive, then it must be true that there is a positive correlation between x and y there is a negative correlation between x and y if x is increased, y must decrease None of the answers is correct.