Page 65, figure 4.2 This figure shows an example of a kernel density estimator (and is the same as page 41, figure 3.5, using the

kdensitycommand. Thewidth(800)option is used to specify the half-width of 800.

use https://stats.idre.ucla.edu/stat/stata/examples/ara/prestige, clear kdensity income, xlabel(0(5000)30000) ylabel(0(.00005).00015) width(800)

Page 66, table at top. You can download

extransfrom within Stata by typingsearch extrans(see How can I use the search command to search for programs and get additional help? for more information about usingsearch).

extrans income----> Variable income: | Transformation | Q1 | Q2 | Q3 |(Q3-Q2)/(Q2-Q1)| |_____________________|__________|__________|__________|_______________| | income |4075 |5930.5 |8206 |1.2263541 | SQRT(income) |63.835728 |77.009518 |90.586975 |1.0306417 | LOG(income) |8.3126259 |8.6878524 |9.0126209 |.86552668 | -1/SQRT(income) |-.01566521|-.01298548|-.01103911|.72633104

Page 66, figure 4.3. Stata cannot quite make a graph just like figure 4.3.

generate lincome = log10(income) kdensity lincome, ylabel(0 1 2)

On page 72, figure 4.7 repeats figure 2.7 from Chapter 2.

graph twoway (lowess prestige income, bwidth(.2) noweight mean) (scatter prestige income), /// xlabel(0(5000)30000) ylabel(0(40)120)

Page 72, figure 4.8. This figure shows performing a cube root transformation on income, and then within

graph twoway, combine the scatter plot, linear regression line and lowess regression line.

generate cr_inc = income^(1/3) graph twoway (lowess prestige cr_inc, bwidth(.2) noweight mean) (lfit prestige cr_inc) /// (scatter prestige cr_inc), xlabel(5(5)30) ylabel(0(40)120)

Page 73, figure 4.9 This shows a

local regressionand scatterplot of mortality by income. In the final scatter overlay, we only scatter observations withmortrate>= 250 and usemlabel(nation)option to portray the outlying nation names.

use https://stats.idre.ucla.edu/stat/stata/examples/ara/leinhard, clear graph twoway (lowess mortrate inc) (scatter mortrate inc) /// (scatter mortrate inc if mortrate >= 250, mlabel(nation)), /// xlabel(0(1000)6000) ylabel(0(250)750)

Page 74, figure 4.10 This graph shows the log of mortality by log of income. Like figure 4.8, this shows the results of a local regression using

lowessand least squares regression usinglfit.

generate linc = log10(inc) generate lmort = log10(mortrate) graph twoway (lowess lmort linc if nation ~="Saudi_Arabia" | nation ~="Libya", bwidth(.5)) /// (lfit lmort linc if nation ~="Saudi_Arabia" | nation ~="Libya") /// (scatter lmort linc if nation ~="Saudi_Arabia" | nation ~="Libya") /// (scatter lmort linc if nation =="Saudi_Arabia" | nation =="Libya", mlabel(nation))

Page 75, figure 4.11 repeats figure 3.14 shown on page 52, as shown below.

use https://stats.idre.ucla.edu/stat/stata/examples/ara/ornstein, clear graph box intrlcks, over(nation) ylabel(0(50)150)

On page 75, the table in the center of the page can be produced using the

tablecommand in Stata. The lower hinge isp25, the median isp50, the upper hinge isp75and the hinge spread is the interquartile range (iqr).

table nation, c(p25 intrlcks p50 intrlcks p75 intrlcks iqr intrlcks)----------+----------------------------------------------------------- Nation of | Control | p25(intrlcks) med(intrlcks) p75(intrlcks) iqr(intrlcks) ----------+----------------------------------------------------------- CAN | 5 12 29 24 OTH | 3 14.5 23 20 UK | 3 8 13 10 US | 1 5 12 11 ----------+-----------------------------------------------------------

Page 76, figure 4.12, skipped for now.

Page 77, figure 4.13 skipped for now.

Page 78, figure 4.14. We convert the percent women to the proportion women, and make a stem and leaf plot of that.

use https://stats.idre.ucla.edu/stat/stata/examples/ara/prestige, clear gen propwomn = percwomn / 100 stem percwomn, round(1)Stem-and-leaf plot for percwomn (% of incumbents who were women) percwomn rounded to integers 0* | 00000111111111111222223334444444 0. | 555667788899 1* | 11112344 1. | 566777 2* | 0144 2. | 568 3* | 0134 3. | 599 4* | 4. | 778 5* | 22 5. | 567 6* | 3 6. | 889 7* | 12 7. | 56667 8* | 334 8. | 9* | 123 9. | 66678

Page 80, figure 4.16. This converts the proportion of women into the

logit, and makes a stem and leaf plot. The Stata stem and leaf plot does not look the same as the one in Fox.

generate pprime = .005 + .99*propwomn generate lgtperc = ln(pprime / (1-pprime)) stem lgtperc, round(.1) lines(2)Stem-and-leaf plot for lgtperc lgtperc rounded to nearest multiple of .1 plot in units of .1 -5* | 33333 -4. | 65555 -4* | 4322210 -3. | 98765 -3* | 4332211000 -2. | 8887755 -2* | 4443210000 -1. | 988777655 -1* | 431111 -0. | 988776 -0* | 44111 0* | 11223 0. | 578899 1* | 11112 1. | 566 2* | 24 2. | 5 3* | 1112 3. | 5