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# Determine the coefficient of x in the expansion of x x x x x x

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a strong massless rope. The other end of the rope is attached to a steel water tank sitting on a flat horizontal concrete surface (see the image to the right). The coefficient of static friction between steel and concrete is 0.45 and the coefficient of kinetic friction between the surfaces is 0.30. The water tank, which is full of water, has sprung a leak. The combined mass of the water and the tank is 500 kg. This mass slowly decreases as the water leaks from the hole. You (i.e. your entire mass) are sitting at rest in the seat. You and the seat will remain at rest as long as the force of static friction is strong enough to hold you. Task: LET [DOWN] and [RIGHT] be positive. Using your knowledge of physics, determine the following: Draw the FBD of the system of you and the chair while at rest. Using the LET statement above, write out the net force equation. [2] Draw the FBD of the system of the water tank at rest on the flat horizontal surface. Using the LET statement above, write out the net force equations for both the vertical and horizontal planes. [3] Using the net force equations, determine the minimum mass of water that must be lost (i.e. leaked out) from the water tank in order for you and the seat to begin falling? [4] As soon as the chair begins to move, static friction between the steel tank and concrete surface becomes kinetic friction. Determine the magnitude of the kinetic friction. [3] Using Newton’s 2nd law, determine the acceleration of the system at the instant that the static friction becomes kinetic friction. [6]
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e idea of “least squares” in regression (you need to fully read pp. 200-208 to understand). 3) What does it mean if b = 0? 4) What does it mean when r-squared is 0? What does it mean when r-squared is 1? 5) What is the difference in an unstandardized regression coefficient and the standardized regression coefficient? 6) If a report says test performance was predicted by number of cups of coffee (b = .94), what does the .94 mean? Interpret this. (For every one unit increase in ___,There is an increase in ___ ) 7) If F (2,344) = 340.2, p < .001, then what is this saying in general about the regression model? (see p. 217) 8) Why should you be cautious in using unstandardized beta? (p. 218) 9) (Ch. 8) Explain partial correlation in your own words. In your explanation, explain how it is different from zero-order correlation (aka Pearson r). 10) (Ch. 9) What is the F statistic used to determine in multiple regression? 11) What is F when the null hypothesis is true? 12) In Table 9.4, which variable(s) are statistically significant predictors? 13) In Table 9.4, explain what it means if health motivation has b = .36 in terms of predicting number of exercise sessions per week. 14) What is the benefit of interpreting standardized beta weights? (see p. 264). 15) What happens if your predictor variables are too closely correlated? 16) Reflect on your learning. What has been the most difficult? How did you get through it? What concepts are still fuzzy to you? Is there anything you could share with me that would help me address how you learn best?
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