variable quantitative, economics homework help

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A description of workers. Each year, the Census Bureau selects a different and random sample of more than 2 million of households to be interviewed in American Community Survey (ACS). The dataset ARIZONA.csv contains information of a small random sample of workers of Arizona interviewed in the ACS 2014. 1 Notes • In your answers use up to one decimal place when the number is not an integer. If the number is close to zero (i.e 0.0006) use up to four decimal places. • Show your work to get full credit. When it corresponds, indicate what statistic function of Excel you used to compute the estimate. • Use the dataset that was assigned. If you use a different dataset, your homework will not be graded. (a) Describe the structure of the data set. In your answers include the population of interest, sample size, number of variables, type of variables (i.e. categorical (nominal/ordinal) or quantitative (discrete/continuous), type of data (i.e., crosssectional, time series, or longitudinal data). (10 points) (b) If each year the Census Bureau interviewed the same sample of households, what would be the type of dataset generated by the ACS in this case? (3 pts). Explain. (c) Describe the workers by computing the estimates of mean, standard deviation, coefficient of variation and skewness of WAGP and JWNP conditional to the gender of the worker (i.e. compute the sample mean of WAGP for males and another sample mean of WAGP for females). Use one of tables available in the word document "TABLES PROBLEM 2" to present your results2. Comment the results. Do not forget to mention the Excel functions you used to compute the statistics. (15 points) 1Source: 2This The American Community Survey Public Use Microdata Sample file is available in the folder HOMEWORK 1 on Blackboard 1 (d) Draw a pie chart to describe the marital status of the workers. You must decide the number of categories that make sense to you (5 pts) (e) Draw a histogram for the earnings variable (you must decide the number of classes and the width). What is the interval with the highest relative frequency? (8 points) (f) Draw a box-plot for earnings by gender (i.e. one box for female and one for male). Use the box-plot to compare the earnings of females and males in terms of measures of location and variability. (8 points) (g) Use Excel to complete the following table (4 points): Sum of deviations for the entire sample .n ¯ 2 i=1 (Wi − W ) .n ¯2 i=1 (Ai − A) .n ¯ ¯ i=1 (Wi − W )(A i − A) W̄ , Ā are the sample mean of WAGP, and AGEP, respectively. You can use the table available in the word document "TABLES PROBLEM 2" to present your results3 (h) Use the previous table (question (f)) to compute the sample correlation between earnings and age. Do NOT use the Excel function CORREL. Provide an interpretation for the value of this estimate. (5 points) (i) Draw a scatter plot using the earnings and age variables (place earnings on the vertical axis). Based on the scatter plot done in (g), could you identify a non linear relationship between earnings and age? If you can, describe such relationship, otherwise explain why a linear relationship would describe that relationship in a better way. ( 6 points) (j) Develop a row percentage table. Use the health insurance status (HICOV2) as the column variable and education as the row variable. Use the following categories for educational attainment: ≤ 15 (Some high school or less), 16-17 (High school graduate or equivalent), 18-19 (some college, no degree), 20 (associate degree), 21 (Bachelor degree), and ≥ 22 (graduate education). Is there any relationship between these two variables? Explain. (11 points) Variables in the dataset: 3This file is available in the folder HOMEWORK 1 on Blackboard 2 • SERIALNO: Household ID • SPORDER: Person ID within the household • W AGP : annual salary in thousand of dollars • SCHL: Educational attainment – 1 .No schooling completed – 2 .Nursery school, preschool – 3 .Kindergarten – 4 .Grade 1 – 5 .Grade 2 – 6 .Grade 3 – 7 .Grade 4 – 8 .Grade 5 – 9 .Grade 6 – 10 .Grade 7 – 11 .Grade 8 – 12 .Grade 9 – 13 .Grade 10 – 14 .Grade 11 – 15 .12th grade - no diploma – 16 .Regular high school diploma – 17 .GED or alternative credential – 18 .Some college, but less than 1 year – 19 .1 or more years of college credit, no degree – 20 .Associate’s degree – 21 .Bachelor’s degree – 22 .Master’s degree – 23 .Professional degree beyond a bachelor’s degree – 24 .Doctorate degree • AGEP :worker’s age 3 • SEX: 1 if worker is male, 2 if worker is female. • HICOV 2: 0= No health insurance; 1=Health insurance through a current/former employer/union or paid by the worker; 2: public health coverage • JW MNP : Travel time to work (in minutes) • MAR:1=Married; 2=Widowed; 3=Divorced; 4 =Separated; 5=Never married/single. 4 SERIALNO SPORDER AGEP 643600 1 908503 1 1040855 1 136871 1 131713 1 1217450 1 885514 1 752974 1 1064267 1 485697 3 207042 2 148501 2 1192890 1 738441 1 81169 2 415015 1 792991 1 735144 1 336380 1 1351073 1 554663 1 400102 1 3642 1 1336472 1 300558 2 1020005 2 2021 3 259370 1 380325 1 1235598 2 952853 2 1236290 2 463325 4 954795 1 1458328 1 706305 1 1363759 1 1430980 1 1136984 2 1020877 1 231106 1 1391980 1 179748 4 1179671 2 1099192 1 830956 1 MAR 63 51 52 30 20 26 54 64 26 29 60 65 48 52 65 28 54 47 55 60 43 53 27 50 56 43 20 39 46 49 37 50 28 36 55 48 43 48 54 45 65 29 29 47 43 34 SCHL 1 1 3 5 5 1 5 1 1 5 1 1 5 2 1 5 1 3 3 1 3 1 5 1 1 3 5 5 5 5 1 1 5 5 3 1 1 1 1 1 3 1 5 1 1 5 SEX 21 13 1 21 19 19 18 21 21 16 16 21 21 21 19 18 21 14 21 22 20 18 21 18 20 18 19 23 22 16 19 22 22 22 21 22 23 20 19 21 16 22 15 22 21 19 WAGP 1 1 2 1 2 1 1 1 1 2 2 1 2 2 1 2 2 1 2 2 1 2 2 2 1 2 1 2 2 1 2 1 2 2 1 2 1 2 2 1 1 1 2 2 2 2 80 26 7.3 60 15 17 35 110 66 39 14.4 60 27.2 17 65 26.2 16 35 124 90 45 30.2 56 100 54 35 10 136 53 25 26 175 38 40 135 58 130 29.6 52 53 12 15.8 28 110 49.4 17 JWMNP HICOV2 10 20 30 45 10 5 35 20 35 35 20 50 20 12 45 45 10 15 60 10 30 35 45 40 10 15 15 5 20 20 20 20 25 10 35 15 10 25 5 50 20 30 20 10 60 60 1 1 0 0 1 1 1 1 1 1 1 2 2 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 2 1 1 0 339311 943711 440191 218284 825897 1095789 184305 448017 1474872 529594 1314823 643435 1085944 1136128 1244472 1055759 440731 20653 1028332 1274535 443994 678148 764973 137026 958599 136579 309409 1480750 43708 1400356 207724 305771 1299839 1223699 1030851 819222 266866 560635 1165721 714861 1432682 396666 664711 630184 387783 117130 1028204 2 2 1 1 2 4 1 1 3 2 1 3 1 3 2 1 1 1 4 1 1 1 2 1 2 2 2 2 1 3 2 2 1 1 2 2 2 1 4 2 3 2 3 2 1 2 4 55 67 32 64 29 44 54 26 55 70 54 23 58 20 50 23 62 51 24 58 46 46 57 34 38 29 43 34 57 41 42 45 31 42 55 64 49 66 19 24 20 32 19 54 64 67 47 1 5 5 3 1 3 1 1 3 1 3 5 1 5 1 5 2 1 5 1 3 3 5 1 5 5 1 5 3 3 1 5 1 3 1 1 1 3 5 5 5 1 5 1 1 1 4 21 16 16 21 21 21 19 16 16 19 19 16 18 20 21 24 10 17 19 21 20 22 21 21 20 21 19 15 22 21 22 16 19 16 23 16 16 19 16 16 16 21 19 21 18 21 22 2 1 1 2 1 2 1 1 2 1 1 1 1 2 2 2 1 2 1 1 2 1 1 1 2 2 2 1 2 1 2 2 2 2 1 1 1 1 1 1 2 2 2 2 1 2 1 68 59 18 62 42 32 180 19 30.4 25 20 1.3 162 10 80 25 8 52 18 309 30 150 5 55 36 60 40 8.4 38 58 50 12 38.6 14 309 60 40 29 27 1.2 12 81 10.8 42 50 34 65 30 6 10 20 25 2 20 10 30 30 15 30 15 5 20 15 15 123 15 60 10 30 15 15 45 20 30 5 8 25 10 30 45 20 5 15 30 20 20 20 30 10 30 35 16 30 25 1 1 1 1 1 1 1 2 1 1 1 0 1 0 1 1 2 1 1 1 1 1 2 1 1 1 1 2 1 1 1 1 1 0 1 0 0 2 1 1 0 1 0 0 1 2 1 1499799 1134261 557082 26986 1146668 1000298 213831 746380 617239 790105 81977 1153134 1069256 216744 992561 209999 1232198 1300009 644053 810386 272794 52654 475260 1264932 1119962 1013525 326623 1047779 424379 119484 341910 1181186 949984 478628 457007 9897 264478 381005 782714 540879 42426 743942 480466 944204 297259 1247269 1460686 1 1 1 1 2 1 2 3 1 1 1 3 2 1 1 2 3 5 2 4 1 2 1 2 3 1 2 1 2 1 3 1 2 3 3 1 2 2 2 1 1 1 4 2 3 3 1 57 29 49 44 84 71 55 27 65 50 62 28 27 56 32 40 17 27 56 19 64 25 53 64 21 27 42 41 52 59 36 31 40 23 33 29 52 41 60 80 37 44 22 62 21 30 39 1 1 1 1 3 1 1 5 1 1 3 5 5 3 5 1 5 5 1 5 5 5 1 1 5 1 1 1 1 3 5 1 1 5 5 5 5 1 1 1 1 5 5 1 5 5 1 19 18 21 21 22 16 21 16 16 18 20 18 17 21 18 19 14 19 16 16 22 21 20 19 18 20 19 21 16 22 22 22 19 20 20 21 18 20 22 21 14 21 19 23 19 16 19 1 1 1 2 2 1 1 2 1 1 1 1 1 2 2 2 2 2 2 1 2 2 2 1 1 1 1 2 2 2 2 1 2 2 1 1 1 2 1 1 1 2 1 2 2 2 1 54 14 67 39 55 63 83 12 16 39 67 20 20 64 11 54 5 14 33 8.4 46 35 27.4 28 23 60 38 60 9 89 20 54 43 5.8 2.4 101 78 78 90 16.5 44 28.1 6 120 12 24 42 15 18 3 20 123 50 5 16 30 30 15 30 25 30 4 35 10 5 5 35 25 30 5 15 10 5 60 45 8 10 30 75 30 20 20 15 30 20 20 45 15 25 15 25 25 60 60 1 1 1 1 0 1 1 1 2 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 2 1 1 0 1 1 1 2 1 2 1 1 1 1 2 0 1 0 1 1 2 1 1294070 452926 403296 413209 905854 384527 92798 1469016 213513 1270074 1067378 720350 252241 1006582 261341 875062 114781 820912 348582 467279 1400392 1317290 603077 584070 402712 1295782 872675 934806 630139 988706 1040402 1339522 522299 1496975 1475777 1499503 1224107 236319 500268 1451482 64171 924824 1310279 828502 1200758 786784 1 1 2 2 1 1 3 2 2 3 1 1 1 1 1 2 1 1 1 1 2 1 2 1 1 1 1 5 2 2 1 1 1 2 1 2 2 1 2 1 1 2 3 3 1 2 40 49 50 50 27 26 38 32 52 21 71 55 55 32 41 49 18 54 21 33 37 54 60 69 54 48 51 24 36 62 44 33 58 46 30 28 24 40 67 36 57 55 52 18 61 50 1 1 1 1 5 3 5 1 1 5 3 1 3 3 3 1 5 5 5 5 1 1 1 3 3 3 2 1 5 1 1 1 5 1 5 3 5 1 1 5 3 1 3 5 2 1 9 19 1 22 21 16 19 14 22 19 22 19 20 20 15 16 16 19 20 14 21 11 22 20 20 19 21 18 16 16 18 16 18 21 17 21 21 19 19 19 21 20 20 14 16 1 2 1 1 2 1 1 2 1 1 1 2 1 2 1 1 2 2 1 2 2 1 1 2 2 2 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 2 2 2 12 80 46 35 90 27.5 39 47 309 9.3 10 70 23 40 19 8 16.4 48 21 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Explanation & Answer

here is my answer

(a) Describe the structure of the data set. In your answers include the population of
interest, sample size, number of variables, type of variables (i.e. categorical
(nominal/ordinal) or quantitative (discrete/continuous), type of data (i.e., crosssectional, time series, or longitudinal data). (10 points)

Population of interest is the annual salary in thousands of dollars (WAGP).
Sample size = 186,
Number of variables = 9,
Type of variables:
• SERIALNO
category = nominal; not quantitative; type of data = cross- sectional
• SPORDER
category = nominal; type of data = cross- sectional
• W AGP
quantitative = continuous; type of data = time series
• SCHL
category = ordinal; type of data = longitudinal survey
• AGEP
quantitative = discrete; type of data = time series
• SEX
category = nominal; type of data = cross- sectional
• HIC OV2
category = ordinal; type of data = longitudinal survey
• JW MNP
quantitative = continuous; type of data = time series

• MAR
category = ordinal; type of data = longitudinal survey
(b) If each year the Census Bureau interviewed the same sample of househ olds, wh at
would be the type of dataset generated by the ACS in this case? (3 pts). Explain.
The type of dataset generated in that case would be longitudinal survey data, as it is
defined as the data that follows the changes of one subject (the sample of households)
over periods o...


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