Happiness ppt (2) (1)

A study on Happiness based on Gender and Occupation

By Team 4

Abinesh Moorthy SAshwini B VBriyanga T GJayavignesh J TNithya VSriram Chandar P SYamini Soundarya B

What is all about Happiness• For every minute you are ANGRY you

lose sixty seconds of your happiness.• True Happiness is to enjoy the present,

without anxious dependence upon the future, not to amuse ourselves with either hopes or fears but to reset satisfied with what we have, which is sufficient, for he that is so wants nothing.

• The Greatest Blessings of Mankind are within us and within our reach. A wise man is content with his lot, whatever it may be, without wishing for what

Happiness• Happiness definitely rules each individual.

Happiness is so important to us, both as individuals and as a world.

• As human beings, although we possess cognitive abilities and are highly "thought" oriented, the quality of our lives is ultimately entirely determined by our emotions.

• Happiness is no mystery. Most people are quite clear about what happiness is, and can easily describe how happy or not they are.

• Most people also consider happiness as their most

important goal in life.

Objectives

• The main objectives are as follows:

– To understand how people are happy and what influences them

– To compare the difference of happiness degree among different

genders and different occupation

– To identify what are all the factors that can affect the happiness

of an individual

Research Methodology• Research Design

– A research design is the arrangement of conditions for collection and analysis of data in a

manner that aims to combine relevance to the research purpose with economy in

procedure.

– The methodology used in project is Descriptive Research.

– The main characteristic of this method is that the researcher has no control over the

variables; one can only report what has happened or what is happening.

• Data Sources:

– Our objective is to find out a real life problem so we opted for primary data.

– Primary data are those which are collected afresh and for the first time, and thus happen

to be the original in character.

– Primary data can be collected through experiment or through survey.

Research Methodology– Survey method was adopted because it helps to procuring data and detailed information from

the respondents.

• Questionnaire:

– A questionnaire consists of a number of questions related to the survey.

– A questionnaire is a research instrument consisting of a series of questions and other prompts

for the purpose of gathering information from respondents.

– Questionnaires are cheap, do not require as much effort from the questioner as verbal or

telephone surveys, and often have standardized answers that make it simple to compile data.

– A 5 scaled - response questionnaire was set up to measure the intensity of a respondent’s

answer.

Google Form

Research Methodology• Sampling:

– The respondents selected should be a representative of the total population as possible in order to produce a miniature cross-selection.

– The selected respondents constitute what is technically called as ‘sample’ and the selection technique is called sampling technique.

– Most predominantly used techniques to select samples are probability sampling and non probability sampling, and we used probability sampling.

– Under probability sampling, we used stratified sampling technique to select the sample. – In stratified sampling, the population is divided into several sub-populations of homogenous

groups.– Sample size refers to the number of respondents selected from the universe to constitute

the sample.– Our sample size was 320.

Factor Analysis– Factor analysis tool is used for analysis and interpretation.

– Factor analysis is used in many fields such as behavioral and social sciences, medicine,

economics, and geography as a result of the technological advancements of computers.

– Large datasets that consist of several variables can be reduced by observing ‘groups’ of variables

called factors.

– It is easier to focus on some key factors rather than having to consider too many variables that

may be trivial, and so factor analysis is useful for placing variables into meaningful categories.

– The basic statistic used in factor analysis is the correlation coefficient which determines the

relationship between two variables.

– The correlation matrix is often used because it is easier to interpret compared to the covariance

tables, although there is not a strict requirement for which matrix to use.

Formulate the Problem

Construct Correlation matrix

Determine model of FA

Determine number of factors

Rotate the factors

Interpret the factors

Calculate factor scores Select the surrogate variable

Determine model fit

Factor Analysis

Components of Factor Analysis• Factor Extraction:

– Factor analysis is based on the common factor model which is a theoretical model.

– This model postulates that observed measures are affected by underlying common

factors and unique factors, and the correlation patterns need to be determined.

– Principal Components analysis is used to extract maximum variance from the data

set with each component thus reducing a large number of variables into smaller

number of components Principal Components produces components whereas

Principal Axis Factor produces factors.

– Principal Components analysis is the first step to reduce the data, then follow-up

with a ‘true’ factor analysis technique.

Components of Factor Analysis• Rotation:

• Factors are rotated for better interpretation since unrotated factors are ambiguous.

• The goal of rotation is to attain an optimal simple structure which attempts to have

each variable load on as few factors as possible, but maximizes the number of high

loadings on each variable.

• Two types of rotation:

– Orthogonal rotation

– Oblique rotation

Components of Factor Analysis• Interpretation of Factor Loadings:

– Factors can be identified by the largest loadings, but it is also important to examine the zero

and low loadings in order to confirm the identification of the factors.

– The signs of the loadings show the direction of the correlation and do not affect the

interpretation of the magnitude of the factor loading or the number of factors to retain.

– Extracting too many factors may present undesirable error variance but extracting too few

factors might leave out valuable common variance.

– So it is important to select which criterion is most suitable to your study when deciding on the

number of factors to extract.

– The eigen values and scree plot are used to determine how many factors to retain.

ANOVA• ANOVA is an abbreviation for the full name of the method: Analysis of Variance Invented by R.A. Fisher

in the 1920’s.

• The one-way Analysis of Variance can be used for the case of a quantitative outcome with a categorical

explanatory variable that has two or more levels of treatment.

Assumptions:

• There are three main assumptions, listed here:

– The dependent variable is normally distributed in each group that is being compared in the one-

way ANOVA.

– There is homogeneity of variances. This means that the population variances in each group are

equal.

– Independence of observations. This is mostly a study design issue and, as such, you will need to

determine whether you believe it is possible that your observations are not independent based on

your study design (e.g., group work/families/etc).

ANOVA Table

Analysis and Interpretation

• Factor analysis allows us to look at groups of variables that tend to be

correlated to each other and identify underlying dimensions that

explain these correlations.

• A group of variables is formed under one factor that explains the

correlations among the variables.

• Statistics associated with factor analysis:

– Kaiser-Meyer-Olkin Measure of Sampling Adequacy

– Bartlett's Test of Sphericity

KMO Table

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .880

Bartlett's Test of Sphericity

Approx. Chi-Square 2829.134

df 210

Sig. .000

Method of Factor Analysis

Scree Plot

Variables Component

1 2 3 4 5I believe that what can go wrong, will go wrong 0.783 I feel lonely 0.78 When I find myself overwhelmed with stress , I completely shut down 0.762 No value can be learned from failure 0.759 There is no point in maintaining close relationships, nothing lasts for ever 0.737

Being myself guarantees that people will dislike me 0.712

Even if I am sure of my decision , I still ask others before making an important or risky decision 0.702

It is better not to raise my hopes so that I don't get disappointed 0.645

I can find good in most disagreeable people 0.466 No matter what life throws at me , I believe that I will deal with it 0.741 When I have a difficult problem , I try to look into different angles in order to come up with a solution 0.703

I know how to calm myself down and relax when my life gets too hectic 0.62

I refuse to give up , no matter how tough things get 0.598 If I ever need help , I believe that my friends / relatives will be there for me 0.529 Given the choice ,I think that the majority of people would choose to do good rather than evil 0.716

I take steps to be happy in most serious situation to overcome it 0.674

When times get tough , I turn to family / friends for support 0.76 Most people can’t be trusted -0.709 I actively keep in touch with family and friends 0.492 I keep my problems to myself 0.783I can find positive even in the most difficult situations -0.462 0.54Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 7 iterations.

Factors Variables Name of the factorFactor 1 No value can be learned from failure Acceptance and being

yourselfNot able to manage Stress and it makes me shutdown completely

Being myself guarantees that people will dislike me

There is no point in maintaining close relationships, nothing lasts for ever

I believe that what can go wrong, will go wrongIt is better not to raise my hopes so that I don't get disappointedEven if I am sure of my decision , I still ask others before making an important or risky decisionI feel lonely

Factor 2 I can find positive even in the most difficult situations ResilienceI know how to calm myself down and relax when my life gets too hectic

No matter what life throws at me , I believe that I will deal with it

I refuse to give up , no matter how tough things getFactor 3 If I ever need help , I believe that my friends / relatives will be there for me Relationship

When times get tough , I turn to family / friends for supportI actively keep in touch with family and friendsI keep my problems to myself

Most people can’t be trustedFactor 4 When I have a difficult problem , I try to look into different angles in order to come up with a

solutionTrying out

I take steps to be happy in most serious situation to overcome it

Factor 5 Most people can’t be trusted Trust Given the choice ,I think that the majority of people would choose to do good rather than evil

ANOVA table for analyzing Factors based on gender

Factors

Sum of Squares

df Mean Square F P value

Acceptance and Being Yourself

Between Groups 2.796 1 2.796

2.812

0.095

Within Groups 316.204 318 0.994Total 319 319

Resilience


2.621

0.106


Relationship


1.037

0.309

Within Groups 317.963 318 1Total 319 319

Trying out


0.073

0.787


Trust


1.454

0.229


ANOVA table for analyzing Factors based on occupation

Factors Sum of Squares df Mean Square F P value

Acceptance and Being Yourself


32.241 .000Within Groups 226.337 315 .719

Total 319.000 319

Resilience


13.102 .000Within Groups 273.497 315 .868

Total 319.000 319

Relationship


15.991 .000Within Groups 265.157 315 .842

Total 319.000 319

Trying out


2.994 .019Within Groups 307.315 315 .976

Total 319.000 319

Trust


21.795 .000Within Groups 249.852 315 .793

Total 319.000 319

Frequency of Respondents

Factors influence based on Gender and Occupations

Conclusion• Many have argued that happiness is the ultimate purpose of human life and that an intrinsic motivation

to pursue it exists.

• The positive psychology movement strives to add to the developing database of knowledge of the

positive aspects of human experience.

• So this study helped us to understand about the various factors of happiness and how it differs from

one occupation to other.

• They are,

– Acceptance and Being yourself

– Resilience

– Relationship

– Trying out

– Trust

Thank you

Happiness ppt (2) (1)

Recruiting & HR

Transcript of Happiness ppt (2) (1)