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- (a) Find the five-number summary, and (b) draw a box-and-whisker plot of the data. 38 85 2 986 95 94 25 29 8 6 6 9 □ (a) Min = 2 (Simplify your answer.) Q₁ = (Simplify your answer.)The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.8 8.2 6.9 3.9 2.3 2.4 2.6 0.6 y 14.2 11.2 10.2 7.5 5.9 6.4 6 4.3 x = thousands of automatic weaponsy = murders per 100,000 residents This data can be modeled by the equation y=0.88x+3.95. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. A) How many murders per 100,000 residents can be expected in a state with 7.2 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 1.6 thousand automatic weapons? Answer = Round to 3 decimal places.Given the values in the following table, what is the slope - intercept form of the data? 4 -2 1 4 O y 3x- 8 Oy=-3x+ 8 Oy 3x - 6 O y = 5x + 9
- Twenty five right-handed students were asked to turn a knob (using their right hands) that moved an indicator by screw action. There were two identical instruments, one with a right-hand thread (the knob turns clockwise) and the other with a left-hand thread (the knob turns counterclockwise). The data presented below gives the times (in seconds) each subject took to move the indicator a fixed distance: Obs. # R 1 2 13 14 15 6 113 105 130 101 138 118 87 IL Obs. #R 137 18 105 9 133 10 108 11 115 12 170 13 103 14 IL |Obs. # |R 116 145 15 118 75 78 16 103 96 107 17 |111 123 122 184 18 104 135 103 148 19 111 112 | 116 147 120 89 193 107 187 121 178 176 1. Test Stat (round off final answer to 4 decimal places) 2. Critical Region: Select one: a. T>abs(2.492) b. T2.492 d. T>abs(2.492) Obs. # R IL 166 22 146 23 100 At 1% level of significance, can we conclude that these right-handed students found it easier to use the knobs with a right-hand thread? Use the following form of the difference:…The ordered pairs below give the winning times (in seconds) of a 100-meter freestyle swim race at a regularly-held competition from 1984 through 2012. (1984, 54.22) (2000, 52.13) (1988, 53.23) (2004, 52.14) (1992, 52.94) (2008, 51.42) (1996, 52.80) (2012, 51.30) (a) Sketch a scatter plot of the data. Let y represent the winning time (in seconds) and let t = 84 represent 1984. (b) Sketch the line that you think best approximates the data and find an equation of the line. (Round the slope and y-intercept to one decimal place.) y = (c) Use the regression feature of a graphing utility to find the equation of the least squares regression line that fits the data. (Round the slope and y-intercept to two decimal places.) y =How to Create a Scatter Plot: 1. Plot each point on the graph, using the values as coordinate points. 2. Draw a line through the points, which shows the general directions of the points. The line should go as much through the middle of all the points as is possible. This is called the line of best fit. The data below shows the temperature and the number of ice creams sold at a particular location on ten different days. Temperature (Celsius) Number of Ice Creams Sold 23 53 17 35 21 48 16 35 18 38 22 52 15 30 18 42 13 19 19 44
- (a) Find the five-number summary, and (b) draw a box-and-whisker plot of the data. 4 8 8529 8 79 6 9 4 2 6 2 9 8779 0 (a) Min = 2 (Simplify your answer.) = 4.25 (Simplify your answer. Do not round.) Q2= 7 (Simplify your answer. Do not round.) Q3 = 8.75 (Simplify your answer. Do not round.) Max = (Simplify your answer.)Enter the data below into lists and graph the scatter plotof the data, using the window [-20, 120] by [0, 80].The ordered pairs below give the winning times (in seconds) of a 100-meter freestyle swim race at a regularly-held competition from 1984 through 2012. (1984, 55.12) (2000, 53.03) (1988, 54.13) (2004, 53.04) (1992, 53.84) (2008, 52.32) (1996, 53.70) (2012, 52.20) (a) Sketch a scatter plot of the data. Let y represent the winning time (in seconds) and let t = 84 represent 1984. (b) Sketch the line that you think best approximates the data and find an equation of the line. (Round the slope and y-intercept to one decimal place.) y = (c) Use the regression feature of a graphing utility to find the equation of the least squares regression line that fits the data. (Round the slope and y-intercept to two decimal places.) y = (d) Compare the linear model you found in part (b) with the linear model you found in part (c). The models are not similar.The models are similar.