TIPS FOR SURVEY DATA ANALYSIS

Presented By:Dr. Michael Kaylen

University of Missouri

INTRODUCTION

• SURVEY DATA ANALYSIS INVOLVES TRANSFORMING SURVEY DATA INTO INFORMATION.

DATA INFORMATION

DATA

INFORMATIONNUMBER OF TRAVELERS IN MO

BY STATE OF ORIGIN AND MONTH.

MONTH_1 MONTH_2 MONTH_3 TOTALMO 1,411,300 1,408,444 663,828 3,483,571IL 498,092 369,995 95,497 963,584KS 261,961 331,999 104,022 697,982AR 148,049 85,801 80,671 314,521CA 181,330 42,411 75,195 298,936OK 162,171 75,132 42,820 280,123TX 60,200 107,057 74,255 241,511OTHER 726,492 739,200 500,286 1,965,978TOTAL 3,449,595 3,160,039 1,636,573 8,246,206

INTRODUCTION

• DATA INFORMATION• TIPS FOCUS ON

EXCEL PIVOT TABLESWEIGHTED DATA

• APPLICATION TO HOUSEHOLD PANEL DATA

• MONTHLY SURVEYS OF HOUSEHOLDS

• 3 LEVELS OF DATAHOUSEHOLD (DEMOGRAPHICS)TRIP (# TRAVELING, STATES VISITED, ETC.)

STATE (# NIGHTS BY LODGING TYPE, EXPENDITURES, ETC.)

• SIMULATED DATA

HOUSEHOLD PANEL DATA

HOUSEHOLD PANEL DATA• HOUSEHOLD LEVEL DATA (HOUSE! - 54,824 OBSERVATIONS) HOUSEHOLD ID MONTH # TRIPS ORIGIN STATE HOUSEHOLD INCOME RANGE TWO WEIGHTS

HOUSEHOLD PANEL DATA• HOUSEHOLD LEVEL DATA• TRIP LEVEL DATA (TRIP! - 21,144

OBSERVATIONS) HOUSEHOLD LEVEL DATA # HOUSEHOLD MEMBERS ON TRIP PRIMARY TRIP PURPOSE PRIMARY TRANSPORTATION MODE (0/1) CODE FOR EACH STATE THREE WEIGHTS

HOUSEHOLD PANEL DATA• HOUSEHOLD LEVEL DATA• TRIP LEVEL DATA• STATE LEVEL DATA (STATE! - 23,225

OBSERVATIONS) HOUSEHOLD AND TRIP LEVEL DATA DETAILED STATE # NIGHTS BY LODGING TYPE EXPENDITURES BY CATEGORY (0/1) CODE FOR ACTIVITIES THREE WEIGHTS

EXCEL PIVOT TABLES

ANALYZE DATA USING 3 OPERATIONS:1.GROUP DATA INTO CATEGORIES• EX. - CREATE A PIVOTTABLE

PUT CURSOR ANYWHERE IN DATA TABLE, WORKSHEET HOUSE.

CLICK ON INSERT TAB

CLICK ON PIVOT TABLE ICON

CLICK OK

To Group: Drag Fields toRow/Column Labels

Cross-tab using both Rowand Column Labels

EXCEL PIVOT TABLES

ANALYZE DATA USING 3 OPERATIONS:1. GROUP DATA INTO CATEGORIES2. SUMMARIZE DATA USINGCALCULATIONS• COUNT, SUM, AVERAGE, MAXIMUM, MINIMUM, STANDARD DEVIATION

• EX.- LOOK AT NUMBER OF HOUSEHOLDS IN SAMPLE, BY STATE OF ORIGIN AND MONTH.

Change the type of calculation by clicking on the drop-down menu

CLICK ON “VALUE FIELD SETTINGS”

Click on Count, then OK

EXCEL PIVOT TABLES

ANALYZE DATA USING 3 OPERATIONS:1. GROUP DATA INTO CATEGORIES

2. SUMMARIZE DATA USINGCALCULATIONS

3. FILTER RESULTSCAN BE USED TO VIEW A

SUBSET OF RESULTS

WEIGHTED DATA

•WEIGHTS ARE USED TO PROJECT SAMPLE DATA TO A POPULATION

EX. – A HOUSEHOLD WEIGHT OF 10,000 MEANS THAT PARTICULAR HOUSEHOLD “REPRESENTS” 10,000 HOUSEHOLDS IN THE POPULATION

WEIGHTED DATA

•THE DESIGN WEIGHT OF A SAMPLE ELEMENT IS THE INVERSE OF ITS INCLUSION PROBABILITY

EX. – IF 20,000 HOUSEHOLDS ARE CHOSEN FROM A SIMPLE RANDOM SAMPLING DESIGN FROM 100,000,000 HOUSEHOLDS, THE DESIGN WEIGHT IS 100,000,000/20,000 = 5,000

WEIGHTED DATA

•CALIBRATION WEIGHTS - COMPUTED USING DATA ON AUXILIARY VARIABLES (E.G., DEMOGRAPHICS)

•“BALANCE” SAMPLE DATA.

EX. – IF STUDYING TRAVEL TO MO AND SAMPLE UNDER-REPRESENTS NEIGHBORING STATES.

WEIGHTED DATA

CALCULATIONS WITH WEIGHTS

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Ex. – To estimate the total number of household trips, create a new variable:

WT_HH * HH_Trips

• To estimate population totals:

PivotTable: Estimated Number of Household Trips, by Month

WEIGHTED DATA

CALCULATIONS WITH WEIGHTS

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• To estimate population averages:

• To estimate population totals:

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PivotTable: Including Sum of Household Weights, by Month

Calculation of Avg. Number of Trips per Household

POTPOURRI

• Monitor sum of weights over all observations, by strata.- Weight totals should reflect population numbers.

• Monitor number of observations, by strata (e.g., month, state).- Sample size is critical to accuracy.

POTPOURRI

Ex. 1 – Sampled Households, but interested in Household Trips (e.g., What percent of all household trips included travel in MO?).

• Be careful projecting to other than the sample design population.

POTPOURRI

- TRIP! contains detailed data on trips, each row (observation) corresponding to one trip.

- Already used data in HOUSE! to estimate 138,511,079 household trips taken during 3 months.

- Problem: household weights over all trips in TRIP! sum to only 124,116,209

POTPOURRI

Sampled households could only provide details for up to 3 trips, regardless of the number of trips actually taken.

Why the discrepancy?

Solution: create a new weight

3,3

*_

3,_

TripsifTripsHHWT

TripsifHHWTWT_HHTrip =

Calculation of WT_HHTrip

PivotTable showing Sum of WT_HHTrip, grouped by TR_VisitMO

About 2.9% of all HH trips included MO.

POTPOURRI

Ex. 1 – Sampled Households, but interested in Household Trips.

• Be careful projecting to other than the sample design population.

Ex. 2 – Sampled Households, but interested in Travelers (e.g., What percent of all travelers visited MO?).

POTPOURRI

- The original data set contains two numbers of potential interest for each detailed trip: the number of people in the travel party and the number of household members in the travel party.

- Problem: which numbers to use?

POTPOURRI

Solution: Since the sampling design was based on households, not travel parties, use the number of household members in the travel party.

WT_PersTrip = WT_HHTrip * TR_HHMemTot

PivotTable showing Sum of WT_PersTrip, grouped by TR_VisitMO

About 2.9% of all travelers visited MO.

Thank You!

Questions, Comments?