STAT 280 Lab 3
What's Your Sign?

The final report for this lab is due one week from now.  Please write up your answers to the questions in a neat, organized fashion and turn in to your lab instructor.

Preliminaries
1. Locate the data: http://www.stat.rice.edu/~hflores/stat280_gmdavis/ and select stat280L2_gss2000.xls

2. About this dataset:
This data was taken from the General Social Survey (with the exception of WEIGHT) in 2002.  Each row represents a person's responses to particular questions.  The normal size of this dataset is 1164 variables (i.e. they asked 1164 different questions on this survey!), but we are going to look at only 3 variables, listed below.

UID
Unique ID.

INCOME
Response is based on the following question asked to the Recipient:  "In which of these groups did your total family income, from all sources, fall last year before taxes?" 

      Under $1,000 	01
      $ 1,000 to 2,999 	02
      $ 3,000 to 3,999 	03
      $ 4,000 to 4,999 	04
      $ 5,000 to 5,999 	05
      $ 6,000 to 6,999 	06
      $ 7,000 to 7,999 	07
      $ 8,000 to 9,999 	08
      $10,000 to 14,999 	09
      $15,000 to 19,999 	10
      $20,000 to 24,999 	11
      $25,000 or over 	12
      Refused, Don't know, No answer, Not applicable {blank}

ZODIAC
Astrological Sign of Respondent

Coded as:
Aries 		01
Taurus 		02
Gemini 		03
Cancer 		04
Leo 		05
Virgo 		06
Libra 		07
Scorpio 	08
Sagittarius 	09
Capricorn 	10
Aquarius 	11
Pisces 		12
Don't know, No answer, Not applicable {blank}

WEIGHT
Exact Weight (rounded to the nearest pound) of Respondent

Project Setup
Suppose that we have a single woman out there on the dating scene called "Shallow Jill".  Jill only wants a man with 2 qualities: thin and rich.  So when Jill walks up to a man and asks the immortal question, "What's your sign?” she really wants to know about how much money he has and what the prospect is of him being thin.  In other words, Jill wants to know if his answers to her question will give her knowledge about weight and income.  Unfortunately, Jill has hired your consulting firm to figure this stuff out.  Lucky you.

ANALYSIS (results, plots and responses to questions are to be neatly included in your lab write-up)
1.  Compute descriptive statistics and histograms for the variables INCOME, ZODIAC, WEIGHT.  Comment on their shape, or other noticeable features about this information.

2.  Compute (INCLUDE ONLY A FEW in your report) histograms for INCOME with respect to each level of ZODIAC.  In other words, compute a histogram for the INCOME variable using only those rows where ZODIAC=01, then again where ZODIAC=02, and so on.  This is tedious, but necessary for you to see what's going on.  Do you notice differences in the ZODIAC distributions with respect to INCOME?

3.  Do the same as (2), except replace INCOME with WEIGHT.  What do you notice across all histograms?

4. Normally distributed variables (or those we suspect as being so) have very nice properties.  You've probably noticed that WEIGHT is nicely (too nicely as a matter of fact) normal.  As such, answer the following questions (these will require TABLE A from your textbook):
•	Given the data and knowledge that a person is Virgo, how likely is it that the person weighs over 200 pounds?  Over 300?
•	Given the data and knowledge that a person is Cancer, how likely is it that the person weighs over 200 pounds?  Over 300?
•	Given the data and knowledge that a person makes over 25,000 a year, how likely is it that the person weighs less than 150 pounds?  Less than 250?  Between 150 and 250?
•	Given the data and knowledge that a person makes over 25,000 a year, how likely is it that the person is Capricorn? (Trick question here)

HINTS for #4: Subset the data and compute Z-statistics (Z-scores) corresponding to the sample mean and sample standard deviation values of the subset.

Conclusions (should also be in your write-up)
Lastly, explain all the stuff you did above, and why it was important.  Specifically, you should touch on the following:

•	Relationships between variables as observed in histograms and descriptive statistics
•	Revelations that (4) gives you.
•	Answer the immortal question!  Does a person's sign make a difference for weight and income based on the data?
•	Comment on the validity of this analysis.  Were the variables appropriate?  Did the analysis make sense?  Make recommendations as to how this analysis might be improved.