Table 3.2, page 37; figure 3.1, page 39 and table 3.3, page 38.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/murder1, clear
/* raw frequency distribution */
tabulate murder
murder rate | Freq. Percent Cum.
------------+-----------------------------------
1.6 | 1 2.00 2.00
1.7 | 1 2.00 4.00
2 | 1 2.00 6.00
2.3 | 1 2.00 8.00
2.9 | 1 2.00 10.00
3 | 1 2.00 12.00
3.1 | 1 2.00 14.00
3.4 | 3 6.00 20.00
3.6 | 1 2.00 22.00
3.8 | 1 2.00 24.00
3.9 | 3 6.00 30.00
4.4 | 1 2.00 32.00
4.6 | 1 2.00 34.00
5 | 1 2.00 36.00
5.2 | 1 2.00 38.00
5.3 | 1 2.00 40.00
5.8 | 1 2.00 42.00
6 | 1 2.00 44.00
6.3 | 1 2.00 46.00
6.4 | 1 2.00 48.00
6.6 | 1 2.00 50.00
6.8 | 1 2.00 52.00
6.9 | 1 2.00 54.00
7.5 | 1 2.00 56.00
8 | 1 2.00 58.00
8.3 | 1 2.00 60.00
8.4 | 1 2.00 62.00
8.6 | 1 2.00 64.00
8.9 | 1 2.00 66.00
9 | 1 2.00 68.00
9.8 | 1 2.00 70.00
10.2 | 2 4.00 74.00
10.3 | 1 2.00 76.00
10.4 | 1 2.00 78.00
11.3 | 2 4.00 82.00
11.4 | 2 4.00 86.00
11.6 | 1 2.00 88.00
11.9 | 1 2.00 90.00
12.7 | 1 2.00 92.00
13.1 | 1 2.00 94.00
13.3 | 1 2.00 96.00
13.5 | 1 2.00 98.00
20.3 | 1 2.00 100.00
------------+-----------------------------------
Total | 50 100.00
recode murder (min/2.9=1 0.0-2.9) (3/5.9=2 3.0-5.9) (6/8.9=3 6.0-8.9) (9/11.9=4 9.0-11.9) ///
(12/14.9=5 12.0-14.9) (15/17.9=6 15.0-17.9) (18/max=7 18.0-20.9), gen(rmurder)
histogram rmurder, discrete xlabel(1(1)7)
tabulate rmurder
RECODE of |
murder |
(murder |
rate) | Freq. Percent Cum.
------------+-----------------------------------
0.0-2.9 | 5 10.00 10.00
3.0-5.9 | 16 32.00 42.00
6.0-8.9 | 12 24.00 66.00
9.0-11.9 | 12 24.00 90.00
12.0-14.9 | 4 8.00 98.00
18.0-20.9 | 1 2.00 100.00
------------+-----------------------------------
Total | 50 100.00
Figure 3.4, page 41.
stem murder Stem-and-leaf plot for murder (murder rate) murder rounded to nearest multiple of .1 plot in units of .1 1* | 67 2* | 039 3* | 0144468999 4* | 46 5* | 0238 6* | 034689 7* | 5 8* | 03469 9* | 08 10* | 2234 11* | 334469 12* | 7 13* | 135 14* | 15* | 16* | 17* | 18* | 19* | 20* | 3
Canada data for figure 3.5, page 43.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/murder2, clear bysort country: stem murder, line(1) ----------------------------------------------------------------------------------------- -> country = USA Stem-and-leaf plot for murder (murder rate) murder rounded to nearest multiple of .1 plot in units of .1 1* | 67 2* | 039 3* | 0144468999 4* | 46 5* | 0238 6* | 034689 7* | 5 8* | 03469 9* | 08 10* | 2234 11* | 334469 12* | 7 13* | 135 14* | 15* | 16* | 17* | 18* | 19* | 20* | 3 ----------------------------------------------------------------------------------------- -> country = Canada Stem-and-leaf plot for murder (murder rate) murder rounded to nearest multiple of .1 plot in units of .1 0* | 7 1* | 123 2* | 023679
Table 3.6, page 46.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/femecon, clear
list
+-----------------------------------------+
| country activity region |
|-----------------------------------------|
1. | austria 60 west europe |
2. | belgium 47 west europe |
3. | denmark 77 west europe |
4. | france 64 west europe |
5. | ireland 41 west europe |
|-----------------------------------------|
6. | italy 44 west europe |
7. | netherlands 42 west europe |
8. | norway 68 west europe |
9. | portugal 51 west europe |
10. | spain 31 west europe |
|-----------------------------------------|
11. | sweden 77 west europe |
12. | switzerland 60 west europe |
13. | united kingdom 60 west europe |
14. | bulgaria 88 east europe |
15. | czech republic 84 east europe |
|-----------------------------------------|
16. | hungary 70 east europe |
17. | poland 77 east europe |
18. | romania 77 east europe |
19. | slovakia 81 east europe |
+-----------------------------------------+
Example 3.4, page 45 and 48.
summarize activity if region==2
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
activity | 6 79.5 6.284903 70 88
summarize activity if region==1
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
activity | 13 55.53846 14.23385 31 77
/* alternative method */
tabstat activity, by(region) stat(n mean sd min max)
Summary for variables: activity
by categories of: region
region | N mean sd min max
------------+--------------------------------------------------
west europe | 13 55.53846 14.23385 31 77
east europe | 6 79.5 6.284903 70 88
------------+--------------------------------------------------
Total | 19 63.10526 16.64297 31 88
--------------------------------------------------------------
/* mean for all of Europe, page 48 */
/* manual computation */
display (13*55.5+6*79.5)/(13+6)
63.078947
/* using the summarize command */
summarize activity
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
activity | 19 63.10526 16.64297 31 88
Example 3.5, page 47.
clear input income 10200 10400 10700 11200 11300 11500 200000 endsave mnincome, replace
summarize income
Variable | Obs Mean Std. Dev. Min Max ————-+——————————————————– income | 7 37900 71481 10200 200000
summarize income in 1/6
Variable | Obs Mean Std. Dev. Min Max ————-+——————————————————– income | 6 10883.33 526.9409 10200 11500
Various medians, page 49.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/mnincome, clear
summarize income, detail
income
-------------------------------------------------------------
Percentiles Smallest
1% 10200 10200
5% 10200 10400
10% 10200 10700 Obs 7
25% 10400 11200 Sum of Wgt. 7
50% 11200 Mean 37900
Largest Std. Dev. 71481
75% 11500 11200
90% 200000 11300 Variance 5.11e+09
95% 200000 11500 Skewness 2.041047
99% 200000 200000 Kurtosis 5.166244
use https://stats.idre.ucla.edu/stat/stata/examples/smss/femecon, clear
tabstat activity, by(region) stat(n mean median)
Summary for variables: activity
by categories of: region
region | N mean p50
------------+------------------------------
west europe | 13 55.53846 60
east europe | 6 79.5 79
------------+------------------------------
Total | 19 63.10526 64
-------------------------------------------
Example 3.6, page 49.
clear
input degree freq
1 38012
2 65291
3 33191
4 7570
5 22845
6 7599
7 3110
end
label define edu 1 "no hs" 2 "hs only" 3 "some coll" 4 "associate" 5 "bachelors" ///
6 "masters" 7 "doctorate"
label values degree edu
tab d [fw = freq]
degree | Freq. Percent Cum.
------------+-----------------------------------
no hs | 38,012 21.40 21.40
hs only | 65,291 36.76 58.16
some coll | 33,191 18.69 76.85
associate | 7,570 4.26 81.11
bachelors | 22,845 12.86 93.97
masters | 7,599 4.28 98.25
doctorate | 3,110 1.75 100.00
------------+-----------------------------------
Total | 177,618 100.00
summarize d [fw = freq], detail
degree
-------------------------------------------------------------
Percentiles Smallest
1% 1 1
5% 1 2
10% 1 3 Obs 177618
25% 2 4 Sum of Wgt. 177618
50% 2 Mean 2.702631
Largest Std. Dev. 1.535418
75% 3 4
90% 5 5 Variance 2.357509
95% 6 6 Skewness .9384876
99% 7 7 Kurtosis 2.990797
Example 3.7, page 51.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/murder1, clear
set obs 51
replace sid=51 in 51
replace state="wash dc" in 51
replace murder=78.5 in 51
summarize murder, detail
murder rate
-------------------------------------------------------------
Percentiles Smallest
1% 1.6 1.6
5% 2 1.7
10% 3 2 Obs 51
25% 3.9 2.3 Sum of Wgt. 51
50% 6.8 Mean 8.727451
Largest Std. Dev. 10.71758
75% 10.4 13.3
90% 12.7 13.5 Variance 114.8664
95% 13.5 20.3 Skewness 5.552901
99% 78.5 78.5 Kurtosis 36.70193
Percentiles, page 53.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/murder1, clear
summarize murder, detail
murder rate
-------------------------------------------------------------
Percentiles Smallest
1% 1.6 1.6
5% 2 1.7
10% 2.95 2 Obs 50
25% 3.9 2.3 Sum of Wgt. 50
50% 6.7 Mean 7.332
Largest Std. Dev. 3.984021
75% 10.3 13.1
90% 12.3 13.3 Variance 15.87242
95% 13.3 13.5 Skewness .7050897
99% 20.3 20.3 Kurtosis 3.420989
/* interquartile range */
display 10.3-3.9
6.4
/* alternative method */
tabstat murder, stat(iqr)
variable | iqr
-------------+----------
murder | 6.4
------------------------
Example 3.8, page 58.
clear
input score sample
0 1
4 1
4 1
5 1
7 1
10 1
0 2
0 2
1 2
9 2
10 2
10 2
end
list
+----------------+
| score sample |
|----------------|
1. | 0 1 |
2. | 4 1 |
3. | 4 1 |
4. | 5 1 |
5. | 7 1 |
|----------------|
6. | 10 1 |
7. | 0 2 |
8. | 0 2 |
9. | 1 2 |
10. | 9 2 |
|----------------|
11. | 10 2 |
12. | 10 2 |
+----------------+
tabstat score, by(sample) stat(n mean sd var)
Summary for variables: score
by categories of: sample
sample | N mean sd variance
---------+----------------------------------------
1 | 6 5 3.34664 11.2
2 | 6 5 5.138093 26.4
---------+----------------------------------------
Total | 12 5 4.134115 17.09091
--------------------------------------------------
Table 3.9, page 62.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/aidsdat, clear
tabulate aids [fw=freq]
aids | Freq. Percent Cum.
------------+-----------------------------------
0 | 1,214 75.97 75.97
1 | 204 12.77 88.74
2 | 85 5.32 94.06
3 | 49 3.07 97.12
4 | 19 1.19 98.31
5 | 13 0.81 99.12
6 | 5 0.31 99.44
7 | 8 0.50 99.94
8 | 1 0.06 100.00
------------+-----------------------------------
Total | 1,598 100.00
sum aids [fw=freq], detail
aids
-------------------------------------------------------------
Percentiles Smallest
1% 0 0
5% 0 1
10% 0 2 Obs 1598
25% 0 3 Sum of Wgt. 1598
50% 0 Mean .4730914
Largest Std. Dev. 1.088548
75% 0 5
90% 2 6 Variance 1.184936
95% 3 7 Skewness 3.170576
99% 5 8 Kurtosis 14.87321
Figure 3.17, page 63.
use https://stats.idre.ucla.edu/stat/stata/examples/smss/murder2, clear graph box murder, over(country)
