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MN 400: Research Methods

PART IV Analysis and

Presentation of Data

Teacher: Pou, Sovann

1

MN 400: Research Methods

CHAPTER 9

Basic data Analysis

2

DATA ANALYSIS

DATA ENTRY

ERROR CHECKING

AND VERIFICATION

CODING

EDITING

Stages of Data Analysis

Chapter 19: Editing and Coding 3

Editing The process of checking for omissions, legibility, consistency

and adjusting the data And readying them for coding and storage

Chapter 19: Editing and Coding

Coding The process of identifying and assigning a numerical

score or other character symbol to previously edited data

4

Birth Year Recorded by Interviewer

1853? 1953 more likely


Editing

IN-HOUSE EDITING

FIELD EDITING


CONSISTENCY

COMPLETENESS QUESTIONS ANSWERED

OUT OF ORDER

Reasons for Editing


• Out of order • DK (do not know)

– Legitimate don’t know

– Reluctant don’t know – Confused don’t

know 7

Codes The rules for interpreting, classifying, and recording data in

the coding process The actual numerical or other character symbols


1a. How many years have you been playing tennis on a regular basis? Number of years: __________

b. What is your level of play?

Novice . . . . . . . . . . . . . . . -1 Advanced . . . . . . . -4 Lower Intermediate . . . . . -2 Expert . . . . . . . . . -5 Upper Intermediate . . . . . -3 Teaching Pro . . . . -6

c. In the last 12 months, has your level of play improved, remained the

same or decreased? Improved. . . . . . . . . . . . . . -1 Decreased. . . . . . . -3

Remained the same . . . . . -2

8

“I believe that people judge your success by the kind of car you drive.”

Strongly agree 1 5 Mildly agree 2 4 Neutral 3 3 Mildly agree 4 2 Strongly disagree 5 1


Tips: Rules for Coding Categories should be exhaustive Categories should be mutually exclusive and independent Coding Open-Ended Responses

Code book Identifies each variable Provides a variable’s description Identifies each code name and position on storage

medium


Data Entry The process of transforming data from the research

project to computers. Recoding is the process of using a computer to

convert original cods used for raw data to codes that are more suitable for analysis. Var1 = 8 - Var1

Error Checking and Verification Data cleaning


Descriptive Analysis The transformation of raw data into a form that will make

them easy to understand and interpret; rearranging, ordering, and manipulating data to generate descriptive information

Chapter 20: Basic Data Analysis: Descriptive Statistics

12

Tabulation Tabulation - Orderly arrangement of data in a table or

other summary format FREQUENCY TABLE

The arrangement of statistical data in a row-and-column format that exhibits the count of responses or observations for each category assigned to a variable

PERCENTAGES CENTRAL TENDENCY

Type of Scale Measure of Measure of Central Tendency Dispersion

Nominal Mode None

Ordinal Median Percentile

Interval or ratio Mean Standard deviation

13

Starbucks Survey 1. Do you know Starbucks? Yes No 2. What coffee shop do you know? Starbucks Coffee World Ban Rai Blue Mountain O Bon Pang Other, specify _________ 3. How many times did you go to Starbucks last month ? Less than 1 time. 1-2 times. 3-4 times. More than 4 times 4. How do the following factors influence your decision to go to Starbucks?

1. Reputation 2. price 3. Atmosphere 4. Service 5. Place 6. Sales promotion 7. Advertisement 8. Taste 9. Quality of products 10. Variety of products

High High High High High High High High High High

__: ____: __: __: __: __: __: __: __:

__: ____: __: __: __: __: __: __: __:

__: ____: __: __: __: __: __: __: __:

__: ____: __: __: __: __: __: __: __:

__: ____: __: __: __: __: __: __: __:

__: ____: __: __: __: __: __: __: __:

Low Low Low Low Low Low Low Low Low Low

5. How do the following Sales promotions influence you to choose Starbucks? 1. Discount Coupon 2. Member Card 3. Premium 4. Collecting point

High High High High

__: ____: __:

__: ____: __:

__: ____: __:

__: ____: __:

__: ____: __:

__: ____: __:

Low Low Low Low

6. In the next time, if you need to go to a coffee shop, will you choose Starbucks? Yes not sure No

Questionnaire: An Example

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Personal Data 7. Gender Male Female 8. Age Less than 20 years old. 20-25 years old. 26-30 years old. 31-35 years old. 36-40 years old. 41-45 years old. 46-50 years old. 51-55 years old. Over 55 years old. 9. Education Primary school. Secondary/high school. Bachelor. Master/ Ph.D. 10. Occupation Student. Employee. Housewife. Governor. Business Owner. Other, specify _________. 11. Income_____________ Baht. Less than 10,000 10,000-20,000 20,001-30000 More than 30,000

Questionnaire: An Example

15

Descriptive data analysis: Sample profile

Gender

37 46.3 46.3 46.343 53.8 53.8 100.080 100.0 100.0

MaleFemaleTotal

ValidFrequency Percent Valid Percent

CumulativePercent

Age

4 5.0 5.0 5.060 75.0 75.0 80.0

8 10.0 10.0 90.02 2.5 2.5 92.52 2.5 2.5 95.02 2.5 2.5 97.52 2.5 2.5 100.0

80 100.0 100.0

Less than 20 years old20 - 25 years old26 - 30 years old31 - 35 years old36 - 40 years old41 - 45 years oldMore than 45 years oldTotal


CumulativePercent

Education

2 2.5 2.5 2.52 2.5 2.5 5.0

73 91.3 91.3 96.33 3.8 3.8 100.0

80 100.0 100.0

High schoolDiplomaBachelor degreeMaster degreeTotal


CumulativePercent

Calculated from total respondents

Calculated from respondents

excluding missing

16

Descriptive data analysis: Sample profile

Occupation

46 57.5 57.5 57.512 15.0 15.0 72.5

2 2.5 2.5 75.08 10.0 10.0 85.09 11.3 11.3 96.31 1.3 1.3 97.52 2.5 2.5 100.0

80 100.0 100.0

StudentsPrivate company officerHouseholdState Enterprise officerBusiness ownerGovernment officerOthersTotal


CumulativePercent

Income

41 51.3 51.3 51.325 31.3 31.3 82.5

7 8.8 8.8 91.37 8.8 8.8 100.0

80 100.0 100.0

Less than 10,000 Baht10,000 - 20,000 Baht20,001 - 30,000 BahtMore than 30,000 BahtTotal


CumulativePercent

Type of customer

37 46.3 46.3 46.343 53.8 53.8 100.080 100.0 100.0

Non-frequent customersFrequent customersTotal


CumulativePercent

17

How many times did you go to Starbucks in the last month?

37 46.3 46.3 46.3

18 22.5 22.5 68.810 12.5 12.5 81.3

15 18.8 18.8 100.0

80 100.0 100.0

Less than 1 timeper week1 t ime per week2 - 3 times per weekMore than 3 timesper weekTotal


CumulativePercent

More than 3 times perweek

2 - 3 times per week1 time per week

Less than 1 time perweek

How often did you go to Starbucks?

Descriptive Statistics

80 1 6 3.30 1.03680 1 5 3.46 .99380 1 5 3.78 1.00680 1 5 3.90 .92280 2 6 3.75 .83480 1 4 3.09 .69780 2 5 3.91 .67980 2 5 4.24 .71680 1 5 4.35 .92980 1 5 3.70 1.10780

ReputationPriceAtmosphereServicesPlaceSales promotionAdvertisementTasteQuality of productsVariety of productsValid N (lis twise)

N Minimum Maximum Mean Std. Deviation

Descriptive data analysis: Items report

Nominal scale data

Interval scale data

18

CROSS-TABULATION

ANALYZE DATA BY GROUPS OR CATEGORIES COMPARE DIFFERENCES CONTINGENCY TABLE PERCENTAGE CROSS-TABULATIONS

How many times did you go to Starbucks in the last month? *Gender Crosstabulation

Count

19 18 37

5 13 183 7 10

10 5 15

37 43 80

Less than 1 timeper week1 time per week2 - 3 times per weekMore than 3 timesper week

How manytimes did yougo to Starbucksin the lastmonth?

Total

Male FemaleGender

Total

19

PERCENTAGE CROSS TABULATION

How many times did you go to Starbucks in the last month? * Gender Crosstabulation

19 18 3751.4% 41.9% 46.3%

5 13 1813.5% 30.2% 22.5%

3 7 108.1% 16.3% 12.5%

10 5 1527.0% 11.6% 18.8%

37 43 80100.0% 100.0% 100.0%

Count% within GenderCount% within GenderCount% within GenderCount% within GenderCount% within Gender

Less than 1 timeper week

1 time per week

2 - 3 times per week

More than 3 timesper week

How manytimes did yougo to Starbucksin the lastmonth?

Total

Male FemaleGender

Total

20

ELABORATION AND REFINEMENT MODERATOR VARIABLE A third variable that, when introduced into an analysis, alters or

has a contingent effect on the relationship between an independent variable and a dependent variable.

SPURIOUS RELATIONSHIP An apparent relationship between two variables that is not

authentic.

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Know these coffee shop Starbucks * Sex of respondent Crosstabulation

5 25 3045 25 7050 50 100

CountCountCount

noyes

Know these coffeeshop Starbucks

Total

male femaleSex of respondent

Total

Know these coffee shop Starbucks * Education of respondent * Sex of respondent Crosstabulatio

Count

1 3 1 54 37 4 455 40 5 50

22 3 141 23 1 36

23 26 1 50

noyes


Totalnoyes


Total

Sex of respondentmale

female

<bachelor bachelor >bachelorEducation of respondent

Total

Elaborative Analysis: an example

22

DATA TRANSFORMATION

Data conversion Changing original form of the data to a new format with a more

appropriate data analysis form Obtained a new variable COLLAPSING A FIVE POINT SCALE: an example

• STRONGLY AGREE • AGREE • NEITHER AGREE OR

DISAGREE • DISAGREE • STRONGLY DISAGREE

• AGREE

• NEUTRAL

• DISAGREE

23

CALCULATING RANK ORDER: Example

Rank the most favorite place you would like to go on your vacation (1=most preference, 4=least preference)

Individual Ranking of dream destinationPerson Hawaii Paris Greece China

123456789

10

1123232143

2324143431

4433331223

3241444314

PreferenceRankings

Destination

1st 2nd 3rd 4th

Calculating Rank Order

HawaiiGreeceParisChina

3132

3211

3532

1235

(3x1)+(3x2)+(3x3)+(1x4) = 22(1x1)+(2x2)+(5x3)+(2x4) = 28(3x1)+(1x2)+(3x3)+(3x4) = 26(2x1)+(1x2)+(2x3)+(5x4) = 30

24

CHARTS AND GRAPHS

PIE CHARTS LINE GRAPHS BAR CHARTS VERTICAL HORIZONTAL

0

20

40

60

80

100

1stQtr

2ndQtr

3rdQtr

4thQtr

EastWestNorth

25

COMPUTER PROGRAMS

SPSS (social package for social science) MICROSOFT EXCEL

Data Interpretation • The process of making pertinent inferences and drawing

conclusions • Concerning the meaning and implications of a research

investigation

26

How to enter Data from the Qualitative

(Open question)

27

Open questions

To analyze the findings, all transcripts were examined and coded according to the key elements and indicators. Sometimes, by using qualitative methods, a direct quote perfectly summarizing or presenting a clear picture of the relationship was used where possible to illustrate the findings.

28

There are many beliefs or rumors reported by the participants in the Focus Group Discussions (FGD). Both men and women report that they have heard by themselves or they are told by their parents or elderly persons in their communities in Phnom Penh and Koh Kong. These beliefs and rumors were also confirmed with Key Informant Interview (KII) in Koh Kong and Phnom Penh.

The belief and rumors were reported during the study are summarised in the table below.

Open questions

29

What are different religious beliefs related to FP exist in your family and community?

30

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