Zagazig university

Faculty of Veterinary Medicine

Session#2:Statistical Analysis of Questionnaire Data

M.Afifi

M.Sc., Biostatistics(Co-Supervision with ISSR, Cairo University) Ph.D., Candidate (AVC, UPEI, Canada)

E-mail: M.Afifi@zu.edu.eg, Afifi-stat6@hotmail.com Tel: +201060658185

Changing the way you look at questionnaire Uses of questionnaire in veterinary research!!!!!!!!!!!!!!

Topics

Questionnaire Data

Data Entry

Data Analysis

Results (Tables + Figures)

Report

Questionnaire Data

Questionnaire Data Consists of group of Major

Items (Construct) assessed by

some questions in order judge

quality of those Constructs

Construct

Single ItemQ1

Likert scale and Data Coding

Likert items are used to measure respondents' attitudes to a particular

question or statement.

Typical familiar five-point Likert scale

5 point Likert scale

3 point Likert scale

Likert scale Data Coding Bipolar scaling method (symmetry), measuring either (+Ve) positive or (-Ve)

negative response to a statement.

Central tendency : 1-2-3-4-5 =3 Sometimes a four-point scale is used; since the middle option of "Neither

agree nor disagree" is not available.

Reverse coding One common validation technique for survey items

is to rephrase a "positive" item in a "negative"

way. When done properly, this can be used to check

if respondents are giving consistent answers.

For example, concerning our SSQ

الله ) شغال الحفظ علي يعتمد الدراسي المقرر ينور...............(

Questionnaire Data Entry

Data Entry

Data Entry

Excel Data Sheet Scanner and OCR

It is preferable to enter data firstly into excel sheet then to be uploaded to

SPSS Open Excel Sheet

Give student ID’s (rows=Cases) for each questionnaire Question No. across (Columns=variables)

Template for Data Entry

Questionnaire Questions

Respondents (Students)

For Example to enter 10 question questionnaire for 40 student this will go

like as follows:

Upload data onto SPSS Open SPSS Click cancel on opening screen

File > Open > Data After your data opens up in SPSS, save it in case you have problems later on

(File > Save as >file name)

Check for what can go wrong in data entry?Max (5)Min (1)

Count (No. of questionnaires)

Data Analysis

Reliability Analysis, Cronbach's Alpha

Reliability coefficient (Cronbach's Alpha)

Measure of internal consistency, that is, how closely related

a set of items are as a group.

Reliability coefficient (Cronbach's Alpha)

Example: compute Cronbach's alpha using SPSS, use a dataset

that contains four test items - q1, q2, q3 and q4 (questionnaire.sav.)

The alpha coefficient for the four items is 0.839, suggesting that the

items have relatively high internal consistency. (Note reliability

coefficient of .70 or higher is considered "acceptable" )

Interpreting Reliability coefficient (Cronbach's Alpha) range from zero (no reliability) -1.00 (perfect reliability). High reliability >>>>questions of a test tended to “pull together.” Students

who answered a given question correctly were more likely to answer other

questions correctly. If a parallel test were developed by using similar items,

the relative scores of students would show little change. Low reliability >>>questions tended to be unrelated to each other in terms

of who answered them correctly. The resulting test scores reflect

peculiarities of the items or the testing situation more than students’

knowledge of the subject matter.

NB:

If a questionnaire includes positively-keyed and

negatively-keyed items, then the negatively-

keyed items must be “reverse-scored” before

computing total scores and before conducting

reliability analysis)

Data Analysis

I. Simple/Basic Statistical analysis

Descriptive Statistics

I. Simple/Basic Statistical analysis

The data analysis decision for Likert items depends on the objective for which

questionnaire was developed development.

If you have a series of individual questions that have Likert response

options for your participants to answer. Modes, frequencies. If you have a series of Likert-type questions that when combined describe

a personality trait or attitude - use means and standard deviations to

describe the scale.

ConstructLikert ScaleSingle Item

Q1

I. Likert-type question (item) Single-item : Each single questions

Frequencies and Distribution each alternative

The number and percentage of students who choose each

alternative are reported. i.e. (% that agree, disagree etc)

Use mode the most frequent

The bar graph on the right shows the percentage choosing each

response

Pooled respondents’ opinions on the statements

Pooled respondents’ opinions on the statements (Questions)

Clustered Bar Chart

Stacked Bar Chart

Medians and Interquartile range Medians: number found exactly in the middle of the distribution a measure of central tendency roughly speaking, it shows what the ‘average’ respondent might

think, or the ‘likeliest’ response.

IQR :a measure of dispersion: it shows whether the responses are

clustered together or scattered across the range of possible

responses.

Example Question of 5 point scale, ranging from “1=strongly disagree” to

“5=Strongly agree”. Were filled by 60 students The number of respondents was as follows

How do I interpret this data???????????????

Data:

Calculating the median This ‘middle’ number is your data ( In case of Odd No.) Two middle numbers the median is half-way between them (In

case of even No.).

Median = 3

Calculating the IQR Use same arrangement of responses that we used above. When

you divide this line into four equal parts, the ‘cut-off’ points are

called quartiles. (IQR = 4 – 3 = 1)

1st Q 3rd Q2nd Q

Interpretation: Reporting the data

Consensus and dissonance

والتنافر التوافق A relatively small IQR (0-1), as was the case above, is an

indication of consensus.

larger IQRs suggest that opinion is polarised, i.e., that your

respondents tend to hold strong opinions either for or against this

topic (dissonance)

For Example Mdn=4, IQR=0 most respondents indicated agreement with the

statement

Mdn=3, IQR=3 If we report that the respondents are, on

average, undecided, that would be a statistical distortion of the data. report more accurately: “Opinion seems to be divided with regard to… .

Many respondents (N=28, 47%) expressed strong disagreement or

disagreement, but a roughly equal number (N=26, 43%) indicated that they

agreed or strongly agreed

Averages (mean) Average = 3.3 something between ‘undecided’ and ‘disagreement’. ‘Our study revealed mild disagreement regarding this Q. This is statistical nonsense not an optimal interpretation. Such an

argument relies on the assumption that the psychological distance

between ‘strong agreement’ and ‘agreement’ is the same as that

between ‘agreement’ and ‘no opinion’..

Don’t use “Ordinal data cannot yield mean values”

Box-plots

Box-plots

II. Composite (summated) scales: Composed of a series of four or more Likert-type items that are combined

into a single composite

Measure concept, e.g. the feeling (social presence) can not be measured

directly also called latent variable. To measure such "soft" implicit

variables with questionnaires, several questions are asked. They then can

be combined into a single composite variable, Created by adding up all the values with a potential score from min (no

amenities) to max (all amenities). Let us look at the central tendency and dispersion of the index

II. Composite (summated) scales: Mean : characterize the center of the data Standard Deviation: measures of variability of the data around the mean

Coefficient of Variation: No. and (%) below and above the average

Data Analysis II. More Elaborate analysis comparison between genders,

Factors impacting student satisfaction Academic achievement pre-enrolment

Social factors

Financial factors

External factors

Work commitments Institutional factors

Worked Example

Assume that we want to asses student satisfaction regarding teaching

4 Questions

60 student

Report (Results ) Tables Figures Interpretation

Frequencies and Distribution each alternative Considering our Questionnaire.sav Analyze >>> Descriptive Stat >>> Frequencies

Frequencies and Distribution each alternative Considering our Questionnaire.sav Analyze >>> Descriptive Stat >>> Frequencies

Frequencies and Distribution each question

Frequencies and Distribution each Q

To get the medians and IQR

Keep in mind your code book

Report (Results )