Aschwin de Wolf approvingly quoted Jonathan Bowden writing “Those who don’t lie down and die soon discover that happiness and intellect are at opposite sides of the pole.” I thought I heard someone debunk that with the GSS before, and set about googling. I replied by linking a comment from Secular Right that I hadn’t actually read before, but I figured I should present the actual results of a GSS analysis.

Frequency Distribution
Cells contain:
-Column percent
-Weighted N
HAPPY
1
VERY HAPPY
2
PRETTY HAPPY
3
NOT TOO HAPPY
ROW
TOTAL
WORDSUM 0 .8
60.7
.7
89.5
1.8
41.9
.8
192.2
1 2.0
152.1
1.4
176.5
3.6
83.8
1.8
412.3
2 3.4
265.8
3.0
384.5
4.3
100.0
3.3
750.3
3 5.8
445.7
5.6
714.2
9.7
224.5
6.1
1,384.4
4 9.2
712.8
10.4
1,321.1
13.0
299.9
10.2
2,333.8
5 15.9
1,230.2
16.5
2,101.5
18.4
424.1
16.5
3,755.8
6 21.1
1,627.4
22.6
2,881.3
19.8
455.8
21.8
4,964.4
7 16.5
1,274.9
16.3
2,075.8
11.3
260.0
15.9
3,610.7
8 11.4
876.2
10.2
1,297.7
7.9
183.4
10.3
2,357.2
9 8.1
623.3
7.8
999.0
5.9
135.6
7.7
1,757.9
10 5.8
444.0
5.6
717.6
4.3
98.1
5.5
1,259.6
COL TOTAL 100.0
7,713.1
100.0
12,758.6
100.0
2,307.0
100.0
22,778.7
Means 6.06 6.05 5.42 5.99
Std Devs 2.15 2.08 2.27 2.13
Unweighted N 7,234 12,774 2,593 22,601

UPDATE: Not everyone is familiar with the meaning of GSS color codes, so here goes:

Color coding: <-2.0 <-1.0 <0.0 >0.0 >1.0 >2.0 Z
N in each cell: Smaller than expected Larger than expected

UPDATE 2: Tyrosine suggested that intelligence may interact with neuroticism to produce unhappiness. The GSS does not include a personality test, but the ANXIOUS variable lists how many of the last seven days the respondent felt anxious/tense. I have lumped responses 0-3 together as the less anxious group and 4-7 as the more anxious group. For those who would like to do something similar themselves, enter the following in the Control field: ANXIOUS(r: 0-3 “Few days anxious”; 4-7 “More days anxious”) The tables for the two groups are below.

Statistics for ANXIOUS = 1(Few days anxious)
Cells contain:
-Column percent
HAPPY
1
VERY HAPPY
2
PRETTY HAPPY
3
NOT TOO HAPPY
ROW
TOTAL
WORDSUM 0 .5 .3 3.8 .6
1 2.3 1.3 6.7 2.1
2 3.2 3.3 5.8 3.5
3 5.4 3.7 3.8 4.3
4 8.8 9.8 15.4 9.9
5 14.7 20.0 19.2 18.1
6 23.5 24.6 16.3 23.6
7 14.7 16.6 10.6 15.4
8 14.4 10.2 8.7 11.5
9 7.7 4.6 4.8 5.7
10 5.0 5.6 4.8 5.3
COL TOTAL 100.0 100.0 100.0 100.0
Means 6.11 6.01 5.20 5.98
Std Devs 2.11 1.94 2.50 2.06
Unweighted N 225 401 65 691

Now for the more anxious:

Statistics for ANXIOUS = 2(More days anxious)
Cells contain:
-Column percent
HAPPY
1
VERY HAPPY
2
PRETTY HAPPY
3
NOT TOO HAPPY
ROW
TOTAL
WORDSUM 0 1.0 .0 1.6 .5
1 .0 1.1 .0 .7
2 1.0 3.6 7.9 3.7
3 8.3 6.9 1.6 6.5
4 10.4 13.5 12.7 12.7
5 18.8 18.9 11.1 17.7
6 11.5 24.4 17.5 20.5
7 17.7 11.3 4.8 11.8
8 10.4 7.3 25.4 10.6
9 16.7 9.8 11.1 11.5
10 4.2 3.3 6.3 3.9
COL TOTAL 100.0 100.0 100.0 100.0
Means 6.30 5.82 6.32 6.00
Std Devs 2.16 2.00 2.40 2.10
Unweighted N 53 153 43 249

I also ran a multiple regression for HAPPY on WORDSUM and ANXIOUS. To do one of those instead of cross-tabs, go to “Analysis” at the top and select the kind of analysis you want. Results are below:

Regression Coefficients Test That Each Coefficient = 0
B SE(B) Beta SE(Beta) T-statistic Probability
WORDSUM -.022 .009 -.076 .032 -2.386 .017
ANXIOUS .052 .009 .188 .032 5.870 .000
Constant 1.802 .061 29.338 .000
Color coding: <-2.0 <-1.0 <0.0 >0.0 >1.0 >2.0 T
Effect of each variable: Negative Positive

You may be initially confused by those results, due to the way HAPPY is coded. Remember that 1 is “Very Happy” while 3 is “Not too happy”. So a “positive” correlation means less happy, as we might expect from the anxious.

On an unrelated note, Matt Steinglass recently used an analogy of Hollywood screenwriter : liberal :: investment banker : conservative. I’m skeptical i-bankers are that conservative, but don’t feel like investigating it right at this moment. Looking up occupational codes for the GSS is a bit of a hassle, I left some links I used to look them up before here. If anyone wishes to do some unpaid labor by investigating them, that would merit kudos.

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