Relative Frequency

Calculate the rate of change between the points labeled on the graph below. (-2, 10) 10 (0, 2) -5 O - 10 10

450 (o0) 400 (4,400) 350 300 (3,300) 250 200 (2,200) 150 100 (1,100) 50 1 2 4 8. Months 10 11 12 Explain whether Account A shows a proportional relationship between months and the amount in the account. Explain whether Account B shows a proportional relationship between months and the amount in the account. Analyze the graph that shows a proportional relationship. Explain the meaning of the points (r, (2, y) and (1, r) where r is the unit rate. Amount in A Accour 3.

Trade Deficit  The graph shows the values I (in billions of dollars) of goods imported to the United States and the values E (in billions of dollars) of goods exported from the United States from 1980 through 2013. Approximate the average rates of change of I and E (in billions of dollars per year) during each period.† A scatter plot titled Trade Deficit has a horizontal axis labeled t = Year (0 ↔ 1980) with values from 0 to 35 and a vertical axis labeled Value of goods (in billions of dollars) with values from 0 to 2,400. There are two groups of points on the scatterplot. The group of points labeled I has 34 points. A pattern goes up and right becoming more steep from (0, 250) to (33, 2,300). The points are as follows.  (0, 250)  (1, 270)  (2, 250)  (3, 270)  (4, 330)  (5, 340)  (6, 370)  (7, 410)  (8, 450)  (9, 480)  (10, 500)  (11, 490)  (12, 540)  (13, 590)  (14, 670)  (15, 750)  (16, 800)  (17, 880)  (18, 920)  (19, 1,040)  (20, 1,230)  (21, 1,150)  (22, 1,170)  (23, 1,270)…

Regression analysis

year, x tuition, y The data in the chart show the cost of tuition at a state university for the years 1997-2001. Fit a regression line to the data, where x is the number of years after 1997. Then find the coefficient of correlation. Finally, use the regression 2. (1999) 10,997 line to predict the cost of tuition in 2007, 2010, and 2013. 0. (1997) 1. (1998) 10,190 9698 3. (2000) 11,416 4. (2001) 11,935

DIRECTIONS : Using the data given below answer the questions based on it. Price (Rs.) Quantity ('000 Kg.) Commodity 2004 2005 2004 2005 Rice 9.3 4.5 100 90 Wheat 6.4 3.7 11 10 3 Pulses 5.1 2.7 Also, E P,9, = 504.2; E P,q, = 1025.9; E P,9, = 450.1; £ P,q, = 916.3.

Retailers are always interested in determining why a customer selected their store to make a purchase. A sporting goods retailer conducted a customer survey to determine why its customers shopped at the store. The results are shown below. Find the percentage of the customers responded that the merchandise was the reason they shopped at the store. Round to the nearest whole percent. Click the icon to view the results of the survey. OA. 50% B. 43% OC. 29% OD. 30% ...

Data Set: {(−3,4), (−2, 3), (−1, 3), (0, 7), (1, 5), (2, 6), (3, 1)} 1. The regression line is: y = -2 FS 0.3 Your Turn: Data Set 2 2. Based on the regression line, we would expect the value of response variable to be 0.005 4. If x= -3.5, the y = 1 when the explanatory variable is 0. 3. For each increase of 1 in of the explanatory variable, we can expect a(n) decrease of 1 in the response variable. ovemple of F6 evtrannlation X O Search MALERINION 8 *. This is an g prt sc home

Frequency 300- 200- 100- 0- Employee Salaries 32 37 42 47 52 57 62 Salary (in thousands of dollars)