Download - Srm group5 sec_a
Team :•Bhavya Roongta (U111013)•Manoj Prabhakaran (U111031)•Mayank Patnaik (U111032)•Moonis Raza (U111134)•Prateek Swain(U111040)•Shrusti Mohanty(U111051)•Sushant Mishra (U111056)•Tarunkanti Nayak (U111059)
SRM Presentation: Effect on Sales of Two-Wheelers with the Advent
of Tata Nano
Topics for DiscussionObjectives
Research Problem
Source of Data
Tools used for Analysis
1
2
5
3
4
A Priori Reasoning and Hypothesis
6 Data Analysis
7 Findings and Conclusion
• To understand and analyze the effect on sales of two-wheelers with the advent of Nano using data analysis tools.
• To identify the level of dependence of buying habits on age, sex, type of city and annual income.
Objectives
“Has the advent of Tata Nano influenced the sales of two wheelers”
Research Problem
A Priori Reasoning and Hypothesis Of Research Problem
A Priori Reasoni
ng
• Having more cash in hand will make the workers more complacent towards their daily work. It will also effect their labor supply at a constant daily wage.
Hypothesis
• HO: There is no relationship between Labor supply and Cash in Hand.
• H1: There is relationship between Labor supply and Cash in Hand
Type and Source of Data
Sources of Data : Survey done through questionnaire
Primary Data : Collected through interview by filling up of a questionnaire by residents of Bhubaneswar
Univariate
Bivariate
Multivariate
Factor
Cluster
Tools Used for Data Analysis
DEMOGRAPHIC VARIABLESTools and Analysis
83%
11%4%2%
Age18-30 years
31-45 years
46-60 years
>60 years
69%
31%
Gender Distribution
MaleFemale
52%
38%
10%Type of city
Tier 1Tier 2Tier 3
UNIVARIATE ANALYSISTools and Analysis
< 250000
250000-400000
400000-550000
550000-700000
700000-1000000
> 1000000
0
5
10
15
20
25
30
35
Annual Income in Rupees
Number of re-spondents
BIVARIATE ANALYSISTools and Analysis
Equation R Square F Constant B1 & Sign B2 & Sign B3 & Sign
Linear .005 .121 1.790 .000(.731)
Logarithmic
.006 .156 1.669 .030(.696)
Quadratic .010 .122 1.730 .001(.886) -9.644E-7(.724)
Cubic .023 .191 1.832 -.001(.902) 9.223E-6(.609)
-1.151E-8(.568)
Independent Variable: Distance TravelledDependant Variable: Nano as an alternative to Two-wheelers
MULTIVARIATE ANALYSISTools and Analysis
Dependent Variable
R Square Constant
Number of persons in a family Family Income Distance travelled
Nano Alternative
.097 1.215(.008) .311(.150) -.020(.921) -.007(.973)
Nano Alternative
.096 1.197(.004).313(.139) Removed -.054(.979)
Nano Alternative
.014 1.766(.000)Removed -.040(.844) .105(.604)
Independent Variable: Distance Travelled, Family Income, Number of persons in a family
Dependant Variable: Nano as an alternative to Two-wheelers
FACTOR ANALYSISTools and Analysis
Variables UsedStyle, Fuel, Safety, Speed, Comfort, Space, Value
Rotated Component Matrix
1 2 3 4Style .820Fuel .815Safety
.663 .547Speed .877ComfortSpace .761Value
.858
FACTOR ANALYSIS-FINDINGSTools and Analysis
1 The component matrix shows that the 7 variables analyzed are divided into four factors. Although, component matrix is not giving a clear picture, but the rotated component matrix classifies the factors into common themes.
2Thus, we get four factors, Factor 1 includes space and value. Hence it can be Practical customer. Similarly, Factor 2 includes fuel and safety. Hence, it can be Cautious customer. Factor 3 includes style and safety, can be Balanced customers and Factor 4 includes only speed, can be speed loving customer.
CLUSTER ANALYSISTools and Analysis
Age
Daily Wage
Number of family
members Optimum
wage
Educational
background Variables
considered for
Clustering
CLUSTER ANALYSIS RESULTSTools and Analysis
Mean values of the variables(rounded off)Variables Cluster 1 Cluster 2 Cluster 3Age 18-30 >60 18-30Gender Male Male Male
Family Income 250000<Income<4000000 >1000000 lac550000<Income<100000
0Type of City Tier 1 Tier 1 Tier 1
• Cluster 1 formed 23% of the entire respondents.
• Cluster 2 formed 5% of the entire respondents.
• Cluster 3 formed 72% of the entire respondents.
Findings From Cluster Analysis
Predominantly males who live in Tier 1 city form the clusters.
The annual family income is the centre differentiating point along clusters.
Thank YouAny Questions?