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- create a model using the first and third point in the data set to get the P for Population in millions. create a model for 3rd and 10th point of the data further below. I need to get the slope, etc. I don't understand the steps for modeling on a subset of the data. M is the slope, etc. Population = mx + b Year Population in millions 1909 90.49 1919 105.063 1929 121.767 this is a subset of the scatter plot for: Year US Population (in millions) 1909 90.49 1919 105.063 1929 121.767 1939 131.028 1949 149.188 1959 177.073 1969 202.677 1979 225.055 1989 247.342 1999 279.295 2009 307.439 2019 328.476There's a roughly linear relationship between the length of someone's femur (the long leg-bone in your thigh) and their expected height, as expressed in the graph below. What does the slope of the line represent? 123455759.56264.56769.57274.57779.50xy0∙Expected Height (centimeters)Femur Length (centimeters) Answer Multiple Choice Answers The femur length for someone with an expected height of 57 centimeters. The expected height for someone with a femur length of 2.5 centimeters. The change in expected femur length for every one additional centimeter of height. The change in expected height for every one additional centimeter of femur length.The marketing manager of a supermarket chain would like to determine the effect of shelf spaceon the sales of pet food. A random sample of 10 stores was selected, and the results are presentedbelow. Store shelf space in cm weekly sales in thousand pesos 1 45 18 2 45 21 3 75 15 4 80 18 5 95 23 6 100 26 7 135 22 8 140 27 9 185 25 10 190 28 a. Determine the slope (?1) and the y-intercept (?0).b. Formulate the estimated simple linear regression equation.c. Illustrate the regression line using a graph.d. Using the estimated simple linear regression equation, estimate the weekly sales when theshelf space is 230cm? 250cm?e. Compute the coefficient of determination and interpret its value.
- Use the computer output to estimate the intercept β0 and the slope β1.The regression equation is Y=816-4.32X. Predictor Coef SE Coef T P Constant 816.348 88.73 9.20 0.000 X -4.324 1.418 -3.05 0.006 Intercept β0: Enter your answer; InterceptSlope β1: Enter your answer; SlopeUse a residual plot to determine if the model y=2.642+0.788x is a good fit for the data in the table below. Justify your answer. x 1.9, 2.1, 2.6, 3.6, 3.8, 4.6, 5.6, 6.2 y 4.3, 4.4, 4.6, 5.4, 5.5, 6.1, 7.1, 7.7 The line is a good fit because the points on the residual plot have a clear pattern. The line is a good fit because the points on the residual plot do not have any noticeable pattern. The line is not a good fit because the points on the residual plot do not have any noticeable pattern. The line is not a good fit because the points on the residual plot have a clear pattern.d) Find the slope, the intercept and the regression equation. e) Find the best predicted height of a person that has a shoe print of 29cm. f) According to the regression equation. For each increment of 1cm in shoe print, what is the increment that we should expect in height? Data SEX AGE FOOT LENGTH SHOE PRINT SHOE SIZE HEIGHT M 67 27.8 31.3 11 180.3 M 47 25.7 29.7 9 175.3 M 41 26.7 31.3 11 184.8 M 42 25.9 31.8 10 177.8 M 48 26.4 31.4 10 182.3 M 34 29.2 31.9 13 185.4 M 26 26.8 31.8 11 180.3 M 29 28.1 31 10.5 175.3 M 60 25.4 29.7 9.5 177.8 M 48 27.9 31.4 11 185.4 M 30 27.5 31.4 11 190.5 M 43 28.8 31.6 12 195 M 54 26.7 31.8 10 175.3 M 31 26.7 32.4 10.5 180.3 M 42 25.1 27.6 9 172.7 M 21 28.7 31.8 12.5 182.9 M 59 29.2 31.3 11 189.2 M 58 27.9 31.3 11.5 185.4 M 42 28.6 34.5 14 193.7 F 47 23.2 24.8 7 165.1 F 19 24.3 28.6 9 166.4 F 20 26 25.4 10 177.8 F 27 23.8 26.7 8 167.6 F 19 25.1 26.7 9 168.3 F 21 25.4 27.9 8.5 165.7 F 32 21.9 27.9 8…
- 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, 54.02) (2000, 51.93) (1988, 53.03) (2004, 51.94) (1992, 52.74) (2008, 51.22) (1996, 52.60) (2012, 51.10) (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=Let y represent the profit (or loss) for a certain company x years after 1960. Based on the data shown below, a statistician calculates a linear model y=1.75x + 14.57What is the relationship between the attendance at a major league ball game and the total number of runs scored? Attendance figures (in thousands) and the runs scored for 12 randomly selected games are shown below. Attendance 55 11 36 57 23 11 24 49 11 37 48 49 Runs 7 -0 9 9 5 5 6 7 2 5 6 10 Use the model to predict the runs scored at a game that has an attendance of 39,000 people.Runs scored = (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: Please select from the following. For every additional thousand people who attend a game, there tends to be an average increase of 0.13 runs scored. As x goes up, y goes up. The slope has no practical meaning since the total number runs scored in a game must be positive. Interpret the y-intercept in the context of the question. Please select from the following.: The average runs scored is predicted to be 2. If the attendance of a baseball game…
- A customer service department asks its customers to rate their over-the-phone service on a scale of 1-20 immediately after their service has been completed. The department then matches each customer's rating with the number of minutes the person waited on hold. The accompanying table shows the ratings and number of minutes on hold for 10 randomly selected customers. Minutes Rating 5 14 8 12 0 17 4 10 6 13 2 15 9 15 2 20 8 14 5 13 The slope is b1= -0.439 The y-intercept is b0=16.455 Calculate the SST. SST= (Round to three decimal places as needed.) The Coast Starlight Amtrak train runs between Seattle and Los Angeles. The table below contains all distances between stops and the typical travel time for each of those distances. DISTANCE BETWEEN STOPS (miles) TIME TO TRAVEL THIS DISTANCE (minutes) 10 52 32 115 40 55 50 61 49 58 56 32 54 31 61 27 84 176 91 322 102 173 112 124 194 64 235 254 246 372 356 195 What is the equation for the best fit line? What is the meaning of the slope in this context? What is the R2R2for the regression line? The distance between LA and Santa Barbara is 102 miles. Use the linear model to predict how long this trip will take. If the actual trip takes 173 minutes, what is the associated residual?the sales recording for nokia mobile phones are given plot the data , also tell about the process of the tiem data series. month jan feb mar apr may june july aug demand 500 510 480 600 600 660 590 700
