south007

Find the derivative of the polynomial;  

how can i earn money

1. Solve the equation 3x + 7 = 22.

avani is building a rectangular play area. the length of the play area is 7.5 meters. the width of the play area is 5.3 meters. is she wants to cover the area in foam, how much foam does she need to buy

Find the solution set for the inequality: 3y+7<16

Find the line y=a+bx whichbest approximates the data points

(7,35),(12,25),(15,13),(12,23),

using least squares.

a= ,
b= .

Linear Algebra Question:

Find the line y=a+bx which best approximates the data points (?4,109),(?2,50),(0,?14),(2,?71),(3,?104).

Find the line y=a+bxy=a+bx which best approximates the data points

Helppp me pls

Average price per square foot of floor area in new one-family houses sold. Price per square foot of floor area excludes value of improved lot Source: Year 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Price per square foot $55.18 $57.41 $60.21 $62.45 $64.38 $66.81 $67.83 $67.70 $70.43 $71.93 $75.68 $79.21 $85.13 $90.63 $91.99 Instead of working on portions of the scatter plots, we want to approximate the data by a line we can use to predict prices in the future. The line that will best fit the given data is called the linear regression. The approximation will be acceptable whether the determina- tion coefficient R (r**2) is close to 1 or the correlation coefficient r is close to -1 or +1.

a) using your entered data to find the equation y = ax + b of the best line through the data points and give the values of coefficients a and b, and of the determination coefficient R or correlation coefficient r.

b. Use Excel to plot the scatter plot and the regression line on the same graph.

c. Is the linear regression a visually good approximation of the data? Sustain your argument by a mathematical proof.

d. use the linear regression to predict the price per square foot area in 2009 e. In what year will the price per square foot be greater than $199?

I have questions. for the first part I don't know the answers.

for the second part, I have problem with (b) What is the correlation coefficient of the regression line?

65. For this dataset, what is the correlation coefficient (r)?

66. What is the regression equation for this dataset?

67. Based on the model (i.e. the regression equation) you just made, predict the perceived pleasantness score for a person who has a percent occupancy score of 70.

I need the answer for part B

PLS HELPP

Step 1: Finding regression equations for the relationship between time and degrees earned.

Below is a table depicting the number of US citizens, in thousands, who earned a bachelor's degree for each year since 2000.

Year:      00      01     02      03      04    05     06        07        08

Male:     530    532   550   573   595  613   631     668       681

Female: 708  712     742   775   804    826   855    895      918

1. a) Use the regression calculator or another tool of your choice to create a scatter plot of the data for men, where the independent variable is the year since 2000 and the dependent variable is the number of people (in thousands). Take a screenshot of your scatterplot and paste it below. If your graph does not include labels, then include a description of what the axes represent.
2. b) Use your calculator to find the regression line y = mx + b for men where x is the number of years since 2000 and y is the number of men. Complete the regression equation below. M(x) =
3. c) Repeat the above steps with the data for women.

Complete the regression equation below.

F(x) =