2. Look at the following scatterplot that shows the relationship between state crime rate and state police expenditure and then respond to the prompts that follow. 160 150 140 130 120 110 100 90 80 70 60 50 40 40 100 110 120 130 140 150 160 50 60 80 90 Crime Rate Expenditure 70

2. Look at the following scatterplot that shows the relationship between state crime rate and state police expenditure and then respond to the prompts that follow. 160 150 140 130 120 110 100 90 80 70 60 50 40 40 100 110 120 130 140 150 160 50 60 80 90 Crime Rate Expenditure 70

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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What level of data is "number of offenses"?
3. These tables show the number of paid admissions to movie theatres in Canada and the population of Canada for 5 years. Paid Admissions to Movie Theatres in Canada Paid Admissions 89 024 000 96 805 000 109 688 000 117 352 000 117 574 000 Year 1996 1997 1998 1999 2000 Population of Canada Population 29 610 757 29 907 172 30 157 082 Year 1996 1997 1998 1999 2000 30 403 878 30 689 035 a) In 1996, the number of movie admissions per capita was 89 024 000 29 610 757, or about 3.0. What does this mean? b) For each year, determine the per capita rate of movie theatre admissions. c) From your results in part b, can you say that Canadians are going to the movies more often? Explain. d) Why is the per capita rate more meaningful than the raw numbers?
22. Construct a cost of living index from the following indices, the weighte being food 55, rent 20, clothing 15, fuel and lighting 15 and miscellaneous 5: Year Food Rent Clothing Fuel and Lighting Miscellaneous 2014 2015 2016 2017 100 105 110 100 104 112 115 100 100 100 101 103 100 110 115 120 98 102 112 105
14. The following table gives the miles per gallon and the load capacity for 6 SUV's. Miles per Gallons Load Сарacity 19 860 17 970 16 1035 16 1165 14 1180 13 1360 a. Develop a scatter diagram for the data. b. How would you characterize the relationship between miles per gallon and load capacity?
The data below lists states poverty rate, gun deaths per 100,000 people, high school graduation rate and the unemployment rate. STATE New Jersey Vermont Minnesota Hawaii Delaware Utah Virginia Nebraska Connecticut Maryland Idaho Alaska Massachusetts Washington Wisconsin Nevada Wyoming Florida North Dakota Pennsylvania lowa Colorado Illinois Missouri South Dakota Michigan New Hampshire Rhode Island Ohio Kansas POVERTY% 6.80% 7.60% 8.10% 8.60% 9.20% 9.20% 9.20% 9.50% 9.70% 9.70% 9.90% 10.00% 10.10% 10.20% 10.20% 10.60% 10.60% 11.10% 11.20% 11.20% 11.30% 11.40% 11.50% 11.60% 11.80% 12.00% 12.00% 12.10% 12.30% 12.50% GUN DEATHS 5.7 9.2 12 2.6 10.3 12.6 10.2 9 4.4 9.7 14.1 17.6 3.1 8.7 9.7 13.8 16.7 11.9 11.8 11.2 8 11.5 8.6 12 10 12 6.4 5.3 11 11.4 H.S. GRAD's 91.8 91 91.5 90.4 87.4 90.4 86.6 89.8 88.6 88.2 88.4 91.4 89 89.7 89.8 83.9 87.4 85.3 90.1 87.9 91.4 89.3 86.4 86.8 89.9 87.9 91.3 84.7 87.6 89.7 UNEMPLOYMENT 5.7 3.6 4 3.5 4.9 3.7 4.5 2.8 5.3 5.1 4.2 6.6 4.7 5.3 4.5 6.8 4 5.3 2.9…
1. The information in the following table shows the amount of sales and the profit from a small retail business in Whitby Ontario for the last 15 years. The years have not been provided as you will only need the amounts. Sales ($) (thousands) Profit ($) (thousands) 195 10 205 15 225 22 240 -10 255 25 300 39 265 24 345 55 295 32 335 37 380 48 405 55 355 50 390 48 410 55 a) Create a scatter plot of the data. Identify any outliers, if they occur. b) Sketch the line of best fit and determine its equation. A c) Describe any correlation you see between the variables. What conclusion could someone make based on the scatter plot? ( d) Identify whether you would use interpolation or extrapolation to predict the profit for the sales amount $500,000 and $230,000. e) Predict the profit for the sales amount $500,000 and $230,000.
Construct the chain indices for the following data. Year Sugar Gur Tea Coffee 2001 88 65 72 89 2002 100 72 64 100 2003 104 73 68 105 | 2004 99 74 79 85
A sales manager collected the following data on annual sales for new customer accounts and the number of years of experience for a sample of 10 salespersons. Years of Annual Sales Salesperson Experience ($1000s) 1 1 80 76 3 82 4 83 8 97 93 10 96 8 12 113 14 121 10 16 119 The data on y= annual sales ($1000s) for new customer accounts and 2 = number of years of experience for a sample of 10 salespersons provided the estimated regression equation ŷ = 68.53+3.31r. For these data 7 = 8.3, (c. I = 206.10, and s = 5.2107. %3D a. Develop the 95% confidence interval for the mean annual sales ($1000s) for all salespersons with eleven years of experience. (2$ ) (to 2 decimals) b. The company is considering hiring Tom Smart, a salesperson with eleven years of experience. Develop a 95% prediction interval of annual sales ($1000s) for Tom yegrs Smart. ($ 24 ) (to 2 decimals) c. Discuss the differences in your answers to parts (a) and (b). As expected, the prediction interval is much (narrow predict…
45. Calculate H.M. from the following data. Values 30-40 40-50 50-60 60-70 70-80 80-90 90-100 Frequency 15 13 8 6 15 15 7 6
For a particular red wine, the following data show the auction price for a 750-milliliter bottle and the age of the wine in June of 2016. Age (years) 37 20 29 33 41 26 29 45 34 22 Price ($) 256 142 217 255 331 168 209 297 237 182
36. Find mode from the following data. older griquong Classes 10- 20- 30- 40- 50- 60- 70- 80-90- 49 59 69 79 89 99 75 156 210 250 42 15 19 29 39 Frequency 6 14 23