Page 130, Table 5.1
use "a:table5.dta", clear rename col1 town rename col2 hours list
+---------------+
| town hours |
|---------------|
1. | A 35 |
2. | A 28 |
3. | A 26 |
4. | A 41 |
5. | A 43 |
|---------------|
6. | A 29 |
7. | A 32 |
8. | A 37 |
9. | A 36 |
10. | A 25 |
|---------------|
11. | A 29 |
12. | A 31 |
13. | A 39 |
14. | A 38 |
15. | A 40 |
|---------------|
16. | A 45 |
17. | A 28 |
18. | A 27 |
19. | A 35 |
20. | A 34 |
|---------------|
21. | B 27 |
22. | B 4 |
23. | B 49 |
24. | B 10 |
25. | B 15 |
|---------------|
26. | B 41 |
27. | B 25 |
28. | B 30 |
29. | RURAL 8 |
30. | RURAL 15 |
|---------------|
31. | RURAL 21 |
32. | RURAL 7 |
33. | RURAL 14 |
34. | RURAL 30 |
35. | RURAL 20 |
|---------------|
36. | RURAL 11 |
37. | RURAL 12 |
38. | RURAL 32 |
39. | RURAL 34 |
40. | RURAL 24 |
+---------------+
Page 131, Figure 5.1
graph hbox hours, by(town) ylabel(0(12)48) ytitle("Hours")
Page 131, the middle of the page
NOTE: Stata 9 does not seem to use string variables as strata variables. We will use the encode command to create a numeric variable that we will call t1 for use as the strata variable.
gen wt = 155/20
replace wt = 62/8 if town == "B"
replace wt = 93/12 if town == "RURAL"
encode town, gen(t1)
svyset [pweight=wt], strata(t1)
pweight: wt
VCE: linearized
Strata 1: t1
SU 1: <observations>
FPC 1: <zero>
svy: mean hours
(running mean on estimation sample)
Survey: Mean estimation
Number of strata = 3 Number of obs = 40
Number of PSUs = 40 Population size = 310
Design df = 37
--------------------------------------------------------------
| Linearized
| Mean Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
hours | 27.675 1.503762 24.62809 30.72191
--------------------------------------------------------------
estat effects
----------------------------------------------------------
| Linearized
| Mean Std. Err. Deff Deft
-------------+--------------------------------------------
hours | 27.675 1.503762 .706547 .840563
sort t1
by t1: tabstat hours, s(n mean p50 sd)
-------------------------------------------------------------------------------------------------------------
-> t1 = A
variable | N mean p50 sd
-------------+----------------------------------------
hours | 20 33.9 34.5 5.94625
------------------------------------------------------
-------------------------------------------------------------------------------------------------------------
-> t1 = B
variable | N mean p50 sd
-------------+----------------------------------------
hours | 8 25.125 26 15.24502
------------------------------------------------------
-------------------------------------------------------------------------------------------------------------
-> t1 = RURAL
variable | N mean p50 sd
-------------+----------------------------------------
hours | 12 19 17.5 9.36143
------------------------------------------------------
Page 135, at the bottom
svy: total hours
(running total on estimation sample)
Survey: Total estimation
Number of strata = 3 Number of obs = 40
Number of PSUs = 40 Population size = 310
Design df = 37
--------------------------------------------------------------
| Linearized
| Total Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
hours | 8579.25 466.1662 7634.708 9523.792
--------------------------------------------------------------