Measure of Central Tendency

There are three measures of central tendency

1. The mean

2. The median

3. The mode

The mean

• The mean or the average, is a measure of central tendency that offers a general picture of the data.

• The mean or average of a set of, say, ten observations, is the sum of ten individual observations divided by ten (the total no of observations).

• (54+50+35+67+50)/5=51.2

The median

• The median is the central item in a group of observations when they are arrayed in either an ascending or a descending order.

• 35,50,50,54,67------50

The mode

• In some cases, a set of observations does not lend itself to meaningful representation through either the mean or the median, but can be signified by the most frequently occurring phenomenon.

• 54,50,35,67,50-----50

Measure of Dispersion

• Dispersion is the variability that exist in a set of observations.

• Two sets of data might have the same mean, but the dispersion could be different.

The three measures of dispersions connected with the mean are

1. The range

2. The variance

3. The standard deviation

The range

• Range refers to the extreme values in a set of observations.

• 54,50,35,67,50

(35,67)

The variance

• The variance is calculated by subtracting the mean from each of the observations in the data set, taking a square of this difference, and dividing the total of these by the number of observations.

The standard deviation

• Another measure of dispersion for interval and ratio scaled data, offers an index of the spread of a distribution or the variability in the data.

• It is a very commonly used, measure of dispersion, and is simply square root of the variance.

Testing Goodness of Data

Goodness of data can be tested by two measures

• Reliability

• Validity

Reliability

• The reliability of a measure is established by testing for both consistency and stability.

• Consistency indicates how well the items measured a concept having together as a set.

Cronbach’s alpha is a reliability coefficient that indicates how well the items in a set are positively correlated to one another

SPSS

• Cronbach Alpha (Reliability)

• Factor Analysis (Validity)

Hypotheses Testing

• Difference between groups

• Relationship between variables

Types of Hypotheses

Null

• that no statistically significant difference exists between the groups

• No Statistically significant relationship exists between variables

Alternative

• logical opposite of the null hypothesis

• that a statistically significant difference does exist between groups

• That statistically significant relationship exists

Testing for Statistical Significance

• State the null hypothesis

• Choose the statistical test

• Select the desired level of significance

• Compute the calculated difference value

• Obtain the critical value

• Usually the software now provides the standard significance values and the f or t values. Based on the significance level value one can interpret the test

• Interpret the test

Research Report Layout

• Title

• Introduction

• A brief literature review

• Research Questions

• Theoretical Framework

• Hypothesis

• Method section

– Study Design (cross sectional , …)

– Population and Sample

– Variables and measures

– Their reliability and Validity

• Data Collection

• Data Analysis

• Discussion of Results

• Recommendations

Primary Data

• Primary Data = information obtained exclusively for current research

• Personal Interview

• Focus Groups

• Panels

• Delphi Technique

• Telephone Interview – Computer assisted telephone interviewing and Computer administered telephone survey

Self-Administered Surveys

Secondary Data

• Company Archives

• Gov Publications

• Industry Analysis

Primary Data Collection Methods

• Focus Group

• Panels

• Interviews (face to face, telephone, electronic media)

• Questionnaires (personally, mail, electronic)

• Observation

• Other (projective tests)

Focus Group:

• Usually consist of 8 to 10 members , with a moderator leading the discussion for 2 hours on a particular topic, concept or product.

• Member are chosen on the bases of their expertise on the topic.

• E.g Discussion on computers and computing , or women mothers , social networking etc

• Less expensive and usually done for exploratory information. Cannot be generalized

Panels:

• Similar to focus group but meets more than once in order to study the change or interventions need to be studies over a period of time.

• Members are randomly chosen

• E.g effect of advertisement of a certain brand need to be assessed quickly, panel members could be exposed to the advertisement and intention of purchase could be assessed.

• When the product is modified then the response of the panel can be observed

Observation measures:

• Methods through which primary data is collected without the involving people.

• E.g: Wear and tear of books , section of an office, seating area of railway station which indicate the popularity, frequency of use etc.

• E.g: The number of cans in the dust bin and their brands, the number of motor cycles vs cars parked in the university parking lot

Interviewing:

• Collect data from the respondent on an issue of interest.

• Usually administered at the exploratory stage of the research.

• In case large set of respondents are needed then more than one interviewer are used , hence they need to be trained so that biases , voice inflections, difference in wording are avoided

• Structured and Unstructured

• Un Structured:

• No planned sequence of questions, help in exploring preliminary issues.

• Structured:

• Know at the outset what information is needed. Focusing on factors relevant to the problem.

• The focus is on the factors which have surfaced during the un structured interview.

Guideline for Interviews

• Listen carefully

• Motivate the respondents

• How to take notes

• Built proper trust and rapport with interviewee

• Clarification of complex issues

• Physical setting

• Explaining the reasons for research and criteria of selection

• Face to Face

• Adv :Clarify doubts, repeating, rephrasing, getting non verbal cues

• Dis : vast resources required, cost, anonymity

Telephone:

• Adv : Wider reach in short time, some time easy to discuss personal information over the phone

• Dis: Can be terminated without warning, cannot have a prolonged interview, non verbal cue.

Closed vs. Open Questions

• Easy.

• Cost of coding is reduced.

• Quicker, standardized interviews.

• Can be answered without thinking.

• Pre-testing is a must.

• Limit the richness of data.

Questionnaires

• Data Collection is mechanism when the researcher knows exactly what is required and how to measure the variables of interest.

• Types of Questionnaire:

– Personally administered questionnaire

– Mail Questionnaire

Personally Administered Questionnaires

• Mostly local area based, org is willing to have a group of employee respond to it.

• It is Cheaper then interviews, helps remove doubts, motivating respondents

Mail Questionnaires:

• Wide geographical area can be reached, respondents have flexibility of time , It is more cost effective but the response rate is low,

• Can improve by giving some incentives and doubts cannot be clarified.

Type and Form of Questions:

– Open ended vs Closed Ended

– Positively vs Negatively Worded

Open ended vs Closed Ended

• In open ended the respondent chooses any way they like. E.g. any five things which interest him at his job.

• In close ended the respondent have to make a choice among the given alternatives e.g. out of the list of 10 job characteristics rank any 5

Positively vs Negatively Worded :

• Have some positive and some negative worded questions to break the monotony.

• E.g. Coming to work is great fun or coming to work is no great fun

Biases in Questions:

Double Barreled:

Questions has more than one question within it.

• E.g. Do you think that the course content is adequate and it applicable at your work?

• Ambiguous Question:

• Respondent does not know what it means. E.g. To what extent would you say you are happy?

• Do you discuss you work with your boss regularly? Do you go to movies frequently?

Recall Dependent:

• Questions based on past experiences and rely on memory.

Leading Questions:

• Are worded in such a way that it would lead the respondent to answer in a way that the researcher would like to or want to give.

Loaded Questions:

• Are when they are phrased in an emotionally charged manner.

• Social Desirability:

• Is when questions are worded such that they elicit(draw out) socially desirable response

Sampling

The process of selecting the right individuals, objects, or events as representative of entire population is known as sampling.

Population

It refers to the entire group of people, events or things of interest that the researcher wishes to investigate.

Element

An element is a single member of a population

Sample

A sample is a subset or subgroup of the population.

Parameters

The characteristics of the population such as the population mean, the population standard deviation, and the population variance are referred to as its parameters.

The Sampling Process

Sampling is the process of selecting a sufficient number of right elements from the population so, the major steps in the sampling include.

1. Defining the population

2. Determine the sample process

3. Determine the sampling design

4. Determine the appropriate sample size

5. Execute the sampling process

Determining the sample design

Two major types of sampling

• Probability sampling

The elements in the population have some known, non zero chances or probability of being selected as sample subjects.

• Non probability sampling

The elements do not have a known or predetermined chance of being selected as subjects.

Probability Sampling

Technique which ensures that each element in the population has an equal chance of being selected for the sample.

• The simple random sampling is the least bias and offer the most generalizability.

• The major advantage of simple random sampling is its simplicity.

• The sampling process could become cumbersome and expensive.

Example: Choosing raffle tickets from a drum, computer-generated selections, random-digit telephone dialing.

Restricted or complex probability sampling:

• It is an alternate to simple random sampling design, several complex probability sampling designs can be used.

• Efficiency is improved in that more information can be obtained for a given sample size using the complex probability sampling procedures.

The most common complex probability sampling design

1. Systematic sampling

2. Stratified sampling

3. Cluster sampling

1. Area sampling

4. Double sampling

Systematic Sampling:

• Technique in which an initial starting point is selected by a random process, after which every nth number on the list is selected to constitute part of the sample.

Stratified Sampling:

• Technique in which simple random subsamples are drawn from within different strata that share some common characteristic. Within the group they are homogenous and among the group they are heterogeneous.

Cluster Sampling

• Technique in which the target population is first divided into clusters. Then, a random sample of clusters is drawn and for each selected cluster either all the elements or a sample of elements are included in the sample.

• Cluster samples offer more heterogeneity within groups and more homogeneity among groups

Area sampling

Specific type of cluster sampling in which clusters consist of geographic areas such as counties, city blocks, or particular boundaries within a locality.

• Area sampling is less expensive than most other sampling designs and it is not dependent on sampling frame.

Double sampling:

• A sampling design where initially a sample is used in a study to collect some preliminary information of interest, and later a subsample of this primary sample is use to examine the matter in more detail

Non-Probability Sampling

Convenience Sampling:

• Sampling technique which selects those sampling units most conveniently available at a certain point in, or over a period, of time.

• Major advantages of convenience sampling is that is quick, convenient and economical; a major disadvantage is that the sample may not be representative.

• Convenience sampling is best used for the purpose of exploratory research and supplemented subsequently with probability sampling.

Judgment (purposive) Sampling:

• Sampling technique in which the business researcher selects the sample based on judgment about some appropriate characteristic of the sample members.

Example: Selection of certain students who are active in the university activities to inquire about the sports and recreation facilities at the university.

Quota Sampling:

This is a sampling technique in which the business researcher ensures that certain characteristics of a population are represented in the sample to an extent which is he or she desires.

Snowball Sampling :

• This is a sampling technique in which individuals or organizations are selected first by probability methods, and then additional respondents are identified based on information provided by the first group of respondents

• The advantage of snowball sampling is that smaller sample sizes and costs are necessary; a major disadvantage is that the second group of respondents suggested by the first group may be very similar and not representative of the population with that characteristic.

Example: Through a sample of 500 individuals, 20 antique car enthusiasts are identified which, in turn, identify a number of other antique car enthuiasts