Consider the data in the table below which was collected from a random sample of 20 vendors at a local open market during the first week after the lockdown period: Vendor Number of years in operation Daily income (NS) 1 > 5 years 1555 2 <1 year 806 3 Between 1 and 5 years 1150 4 Between 1 and 5 years 1350 5 > 5 years 1790 Between 1 and 5 years 1660 7 <1 year 505 8. > 5 years 1950 9 Between 1 and 5 years 2240 10 > 5 years 1811 11 Between 1 and 5 years 1904 12 > 5 years 2209 13 <1 year 1600 14 > 5 years 2010 15 Between 1 and 5 years 2300 16 Between 1 and 5 years 300 17 <1 year 549 18 > 5 years 662 19 Between 1 and 5 years 1444 20 <1 year 755 Required: Construct a cross-tabulation between the random variables Daily Income and Number of years in Operation and provide an interpretation.

Consider the data in the table below which was collected from a random sample of 20 vendors at a local open market during the first week after the lockdown period: Vendor Number of years in operation Daily income (NS) 1 > 5 years 1555 2 <1 year 806 3 Between 1 and 5 years 1150 4 Between 1 and 5 years 1350 5 > 5 years 1790 Between 1 and 5 years 1660 7 <1 year 505 8. > 5 years 1950 9 Between 1 and 5 years 2240 10 > 5 years 1811 11 Between 1 and 5 years 1904 12 > 5 years 2209 13 <1 year 1600 14 > 5 years 2010 15 Between 1 and 5 years 2300 16 Between 1 and 5 years 300 17 <1 year 549 18 > 5 years 662 19 Between 1 and 5 years 1444 20 <1 year 755 Required: Construct a cross-tabulation between the random variables Daily Income and Number of years in Operation and provide an interpretation.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

5. The following table was presented in an article summarizing a study to compare a new drug to a standard drug and to a placebo. Standard Drug 44.9 (5.1) Characteristic* New Drug Placebo Age, years 45.2 (4.8) 42.8 (4.3) 0.5746 % Female 51% 55% 57% 0.1635 Annual Income, $000s 59.5 (14.3) 63.8 (16.9) 58.2 (13.6) 0.4635 % with Insurance 87% 65% 82% 0.0352 Disease Stage 0.0261 35% 18% 33% Stage I Stage II Stage III *Table entries and Mean (SD) or % 42% 37% 47% 23% 51% 20% a) Are there any statistically significant differences in the characteristics shown among the treatments? Justify your answer.
4. Students in Miss Bigelow's English class completed a vocabulary test worth 100 points, and, interestingly, all students received different scores on this test. When Miss Bigelow summarized the test scores, she obtained the following: Minimum = 25 points, Q, = 59 points, Median = 78 points, Q3 = 87 points, and Maximum = 100 points. If Kami's score on this test is at the 40th percentile, what does this mean? A. Kami's test score is between 25 points and 59 points. B. Kami's test score is between 59 points and 78 points. C. Kami's test score is between 78 points and 87 points. D. Kami's test score is between 87 points and 100 points. E. Kami had a higher test score than 60% of her classmates.
41. Nineteen immigrants to the U.S were asked how many years, to the nearest year, they have lived in the U.S. The data are as follows: 2; 5; 7; 2; 2; 10; 20; 15; 0; 7; 0; 20; 5; 12; 15; 12; 4; 5; 10. Table 1.15 was produced. Data O 2 4 5 7 10 12 15 20 Frequency Relative Frequency 2 3 3 2 2 2 1 1 № 19 3 19 19 3 10 份 2 19 19 19 2 19 1 19 19 Cumulative Relative Frequency 0.1053 0.2632 0.3158 0.4737 0.5789 0.6842 0.7895 0.8421 1.0000 Table 1.15 Frequency of Immigrant Survey Responses M Fix the errors in Table 1.15. Also, explain how someone might have arrived at the incorrect number(s). b. Explain what is wrong with this statement: "47 percent of the people surveyed have lived in the U.S. for 5 years." c. Fix the statement in b to make it correct. d. What fraction of the people surveyed have lived in the U.S. five or seven years? e. What fraction of the people surveyed have lived in the U.S. at most 12 years? f. What fraction of the people surveyed have lived in the U.S. fewer than 12…
4) The table shows, for the years 1997–2012, the mean hourly wage for residents of the town of Pity Me and the mean weekly rent paid by the residents. Mean hourly wage (dollars) Mean hour. Mean weekly rent (dollars) Mean weekly rent (dollars) Year Year (dollar 116 1997 57 10.38 2005 28.99 59 113 1998 10.89 2006 28.63 2007 1999 62 11.96 112 36.75 14.55 2000 63 12.46 2008 86 17.90 2001 86 17.72 2009 90 2002 2010 119 28.07 90 14.67 131 35.24 2003 2011 17.97 100 122 2004 2012 22.23 31.87 115 Find the least squares line that uses mean hourly wage to predict mean weekly rent. Round values to the nearest ten-thousandth. Include a scatter plot with the regression lino
The Bureau of Labor Statistics reports on a variety of employment statistics. "College Enrollment and Work Activity of 2004 High School Graduates" provides information on high school graduates by gender, by race, and by labor force participation as of October 2004.³ (All numbers are in thousands.) The following two tables provide information on the “Labor force status of persons 16 to 24 years old by educational attainment and gender, October 2004." Using the information contained in the tables, do Exercises 4.58 through 4.62. OS LabForce Women, Age 16 to 24 < High School HS degree Some college Civilian Labor Force Employed Unemployed 662 2,050 1,352 Bachelors degree or more 921 Column Total 4,985 For Males: P{CLF | HSD} P{CLF | BD} 205 334 126 Click here for the Excel Data File 55 720 For Females: P{EMPI (CLF and HSD)} P{EMP | (CLF and BDM)} P{CLF | HSD} P{CLF | BD} Not in Labor Force 759 881 321 105 2,066 P{EMPI (CLF and HSD)} P{EMPI (CLF and BDM)} Row Total 1,626 3,265 1,799…
The table below shows the number of fatal heart attacks in 19 selected European Union countries during 2014 along with the 2014 debt-to-GDP ratios for these countries in 2014. Compare the coefficients of variation and comment on your findings. Country Fatal Heart Attacks 2014* Debt to GDP Ratio** 1 Austria 14,521 225% 2 Belgium 7,792 327% 3 Czech Republic 26,171 128% 4 Denmark 3,943 302% 5 Finland 10,338 238% 6 France 33,513 280% 7 Germany 121,471 188% 8 Greece 12,200 317% 9 Hungary 32,138 225% 10 Ireland 4,283 390% 11 Italy 69,653 259% 12 Netherlands 8,956 325% 13 Poland 38,642 134% 14 Portugal 7,456 358% 15 Romania 50,667 104% 16 Slovakia 13,381 151% 17 Spain 32,564 313% 18 Sweden 12,617 304% 19 United Kingdom 69,325 252%
Consider that we are interested in computing the time weighted average number of cars parked in the parking garage on a Sunday in December. We start at midnight and collect the entry and exit times of cars in the garage until the following midnight as follows. Entry 12:45:00 AM Entry 1:00:00 AM Entry 3:30:00 AM Exit 5:15:00 AM Entry 7:00:00 AM Entry 8:15:00 AM Exit 8:45:00 AM Entry 10:00:00 AM Exit 10:30:00 AM Entry 2:30:00 PM Exit 4:15:00 PM Entry 6:00:00 PM Exit 7:45:00 PM Entry 9:30:00 PM Exit 11:15:00 PM What was the time weight average number of cars parked in the parking garage on that Sunday?
An article included the accompanying data on 17 fish caught in 2 consecutive years. Year FishNumber Weight(g) Length(mm) Age(years) Year 1 1 777 410 9 2 581 368 11 3 540 357 15 4 647 373 12 5 537 361 9 6 892 385 9 7 674 380 10 8 782 400 12 Year 2 9 570 407 12 10 628 410 13 11 728 421 12 12 866 446 19 13 1,043 478 19 14 803 441 18 15 833 454 12 16 765 440 12 17 728 427 12 (a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x1 for length and x2 for age. Round your numerical values to two decimal places.) = (b) Carry out the model utility test to determine whether at least one of the predictors length and age are useful for predicting weight. Use a significance level of 0.05. Calculate the test statistic and find the P- value. (Round your answer to two decimal places.) F = P-value =
The racial/ethnic diversity of post high school students enrolled at MVCC during the fall 2020 semester is given below. Racial/Ethnic Diversity of Post High School Students Race/Ethnicity Percent* American Indian or Alaska Native 0.4% Asian 5.3% Black or African American 9.6% Hispanic or Latino 9.6% Two or more races 2.8% Native Hawaiian or Pacific Islander <0.1% Non-Resident Alien 0.5% Unknown 1.5% White 70.2% (*Percentages may not total 100 due to rounding) What is the race/ethnicity of the majority of students at MVCC? What total percent of students were either Black or African American or Hispanic or Latino? There were 3,444 students enrolled at MVCC at the time of the study. How many (not percent) students were Asian? (The answer must be a whole number.)
The following data represents the age of 30 lottery winners. Given the frequency distribution for the data, Age Frequency Relative Frequency Cumulative Relative Frequency [20,29] 1 0.0333 0.0333 [30,39] 5 0.1667 0.2 [40,49] 7 0.2333 0.4333 [50,59] 5 0.1667 0.6 [60,69] 10 0.3333 0.9333 [70,79] 1 0.0333 0.9666 [80,89] 1 0.0333 0.9999 What is the frequency of lottery winners of age between 19 and 40? What percentage of lottery winners are 70 years or older? % What is the relative frequency of ages under 40? What is the cumulative relative frequency of lottery winners younger than 50?
Complete the stemplot for the following data. 29 27 19 25 10 21 33 23 38 15 23 30 13 19 23 13 22 38 28 24 31 29 42 22 46 19 13 28 45 23 1# | 033359992# | 122333345788993# | 013884# |
6. As a researcher for an environmental agency, you have been asked to determine if the air quality in the Philippines has changed over the past 2 years. You select a random sample of 7 metropolitan cities and find the number of days each year that these cities failed to meet acceptable air quality standards. The results were given below. Can we conclude that after a year, there is no improvement in the air = 0.15. quality in the Philippines? Use a = City Year 1 Year 2 1 18 24 2 50 77 3 9 13 4 22 21 5 30 44 6 29 23 7 1 6