2083245,Shahrukh Mehmood

8/2/2019 2083245,Shahrukh Mehmood

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+++++++Frequencies

Notes

Output Created 15-Dec-2011 17:40:03

Comments

Input Data C:\Users\Farrukh\Documents\Untitled1.sav

Active Dataset DataSet1

Filter

Weight

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N of Rows in Working Data File 50

Missing Value Handling

Definition of Missing User-defined missing values are treated as

missing.

Cases Used

Statistics are based on all cases with valid

data.

Syntax FREQUENCIES VARIABLES=sex age

educationalit basicneed usephone brandofcell

typesofphone purposeofusage internetwap

faouritewap situationusephone

condiationswitchoff annoyingphone

providelongbattery reasonableprices

/ORDER=ANALYSIS.

Resources Processor Time 00 00:00:00.047

Elapsed Time 00 00:00:00.047

Statistics

sex

age of

respondent

educational it

related

is this our basic

need use cell phone

which brand of

cell use

which type of

phone use

which pupose of

use cell phone

for what you

use internet

what is your

favourite wap

in what situation

you dont use

cell phone

in what

condiation u

switch off phone

in which

situation you

annoying cell

phone

what ce

provide you

battery

N Valid 50 50 50 50 50 50 50 50 50 50 50 50 50

Missing 0 0 0 0 0 0 0 0 0 0 0 0 0


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Frequency Table

sex

Frequency Percent Valid Percent

Cumulative

Percent

Valid male 36 72.0 72.0 72.0

female 14 28.0 28.0 100.0

Total 50 100.0 100.0

age of respondent


Cumulative

Percent

Valid less dn 17 1 2.0 2.0 2.0

18-20 14 28.0 28.0 30.0

21-23 31 62.0 62.0 92.0

24-26 4 8.0 8.0 100.0

Total 50 100.0 100.0

educational it related


Cumulative

Percent

Valid yes 22 44.0 44.0 44.0

no 26 52.0 52.0 96.0

4 2 4.0 4.0 100.0

Total 50 100.0 100.0

is this our basic need


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Cumulative

Percent

Valid yes 44 88.0 88.0 88.0

no 4 8.0 8.0 96.0

3 2 4.0 4.0 100.0

Total 50 100.0 100.0

use cell phone


Cumulative

Percent

Valid yes 48 96.0 96.0 96.0

no 2 4.0 4.0 100.0

Total 50 100.0 100.0

which brand of cell use


Cumulative

Percent

Valid nokia 31 62.0 62.0 62.0

samsung 9 18.0 18.0 80.0

apple 5 10.0 10.0 90.0

others 5 10.0 10.0 100.0

Total 50 100.0 100.0

which type of phone use


Cumulative

Percent

Valid touchph 17 34.0 34.0 34.0

sldeph 5 10.0 10.0 44.0

flipph 6 12.0 12.0 56.0

smartph 22 44.0 44.0 10 0.0

Total 50 100.0 100.0


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which pupose of use cell phone


Cumulative

Percent

Valid voice call 17 34.0 34.0 34.0

sms 20 40.0 40.0 74.0

internet 6 12.0 12.0 86.0

to show off 7 14.0 14.0 100.0

Total 50 100.0 100.0

for what you use internet


Cumulative

Percent

Valid news paper 5 10.0 10.0 10.0

weather shopping 5 10.0 10.0 20.0

travel service 1 2.0 2.0 22.0

others 39 78.0 78.0 100.0

Total 50 100.0 100.0

what is your favourite wap


Cumulative

Percent

Valid google 20 40.0 40.0 40.0

facebook 22 44.0 44.0 84.0

youtube 7 14.0 14.0 98.0

orkut 1 2.0 2.0 100.0

Total 50 100.0 100.0


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in what situation you dont use cell phone


Cumulative

Percent

Valid when you are getting bore 14 28.0 28.0 28.0

13 1 2.0 2.0 30.0

in emergency 17 34.0 34.0 64.0

missing some one 10 20.0 20.0 84.0

other issues 8 16.0 16.0 100.0

Total 50 100.0 100.0

in what condiation u switch off phone


Cumulative

Percent

Valid in class 24 48.0 48.0 48.0

at meeing 7 14.0 14.0 62.0

in mosque 11 22.0 22.0 84.0

others 8 16.0 16.0 100.0

Total 50 100.0 100.0

in which situation you annoying cell phone


Cumulative

Percent

Valid in office or at work 10 20.0 20.0 20.0

ina car or bus 9 18.0 18.0 38.0

mosque 17 34.0 34.0 72.0

others 14 28.0 28.0 100.0

Total 50 100.0 100.0

what cell provide you ong battery


Cumulative

Percent


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Valid nokia 34 68.0 68.0 68.0

apple 6 12.0 12.0 80.0

samsung 8 16.0 16.0 96.0

others 2 4.0 4.0 100.0

Total 50 100.0 100.0

which brand of cell ph give reasonable pricess


Cumulative

Percent

Valid nokia 36 72.0 72.0 72.0

samsung 5 10.0 10.0 82.0

china mobile 6 12.0 12.0 94.0

others 3 6.0 6.0 100.0

Total 50 100.0 100.0

Descriptives

Notes


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Missing Value Handling Definition of Missing User defined missing values are treated as

missing.

Cases Used All non-missing data are used.


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Syntax DESCRIPTIVES VARIABLES=sex age

educationalit basicneed usephone brandofcell

/STATISTICS=MEAN STDDEV MIN MAX.


Elapsed Time 00 00:00:00.000

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

sex 50 1 2 1.28 .454

age of respondent 50 1 4 2.76 .625

educational it related 50 1 4 1.64 .693

is this our basic need 50 1 3 1.16 .468

use cell phone 50 1 2 1.04 .198

which brand of cell use 50 1 4 1.68 1.019

Valid N (listwise) 50

PPlot

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Missing Value Handling Definition of Missing User-defined missing values are treated as

missing.

Cases Used For a given sequence or time series variable,

cases with missing values are not used in the

analysis. Cases with negative or zero values

are also not used, if the log transform is

requested.

Syntax PPLOT

/VARIABLES=sex age

/NOLOG/NOSTANDARDIZE

/TYPE=P-P

/FRACTION=BLOM

/TIES=MEAN

/DIST=NORMAL.


Elapsed Time 00 00:00:01.670

Use From First observation

To Last observation

Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

Saving New Variables NEWVAR = CURRENT

Maximum Number of Lags in

Autocorrelation or PartialAutocorrelation Plots

MXAUTO = 16

Maximum Number of Lags Per

Cross-Correlation Plots

MXCROSS = 7

Maximum Number of New

Variables Generated Per

Procedure

MXNEWVAR = 60

Maximum Number of New Cases

Per Procedure

MXPREDICT = 1000

Treatment of User-Missing

Values

MISSING = EXCLUDE

Confidence Interval Percentage

Value

CIN = 95

Tolerance for Entering Variables

in Regression Equations

TOLER = .0001


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Maximum Iterative Parameter

Change

CNVERGE = .001

Method of Calculating Std. Errors

for Autocorrelations

ACFSE = IND

Length of Seasonal Period Unspecified

Variable Whose Values Label

Observations in Plots

Unspecified

Equations Include CONSTANT

Model Description

Model Name MOD_2

Series or Sequence 1 sex

2 age of respondent

Transformation None

Non-Seasonal Differencing 0

Seasonal Differencing 0

Length of Seasonal Period No periodicity

Standardization Not applied

Distribution Type Normal

Location estimated

Scale estimated

Fractional Rank Estimation Method Blom's

Rank Assigned to Ties Mean rank of tied values

Applying the model specifications from MOD_2


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Case Processing Summary

sex age of respondent

Series or Sequence Length 50 50

Number of Missing Values in the

Plot

User-Missing 0 0

System-Missing 0 0

The cases are unweighted.

Estimated Distribution Parameters


Normal Distribution Location 1.28 2.76

Scale .454 .625


sex


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This data shows that data is not normal and his tail is positive.


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Age of respondent


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This pp plot shows that the data is almost normal and its curved


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PPlot

Notes


Comments



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Date

Missing Value Handling Definition of Missing User-defined missing values are treated as

missing.

Cases Used For a given sequence or time series variable,

cases with missing values are not used in the

analysis. Cases with negative or zero values

are also not used, if the log transform is

requested.

Syntax PPLOT

/VARIABLES=sex age

/NOLOG

/NOSTANDARDIZE

/TYPE=Q-Q

/FRACTION=BLOM

/TIES=MEAN

/DIST=NORMAL.


Elapsed Time 00 00:00:01.668

Use From First observation

To Last observation

Time Series Settings (TSET) Amount of Output PRINT = DEFAULT

Saving New Variables NEWVAR = CURRENT

Maximum Number of Lags in

Autocorrelation or Partial

Autocorrelation Plots

MXAUTO = 16

Maximum Number of Lags Per

Cross-Correlation Plots

MXCROSS = 7


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Maximum Number of New

Variables Generated Per

Procedure

MXNEWVAR = 60

Maximum Number of New Cases

Per Procedure

MXPREDICT = 1000

Treatment of User-Missing

Values

MISSING = EXCLUDE

Confidence Interval Percentage

Value

CIN = 95

Tolerance for Entering Variables

in Regression Equations

TOLER = .0001

Maximum Iterative Parameter

Change

CNVERGE = .001

Method of Calculating Std. Errors

for Autocorrelations

ACFSE = IND

Length of Seasonal Period Unspecified

Variable Whose Values Label

Observations in Plots

Unspecified

Equations Include CONSTANT

Model Description

Model Name MOD_3

Series or Sequence 1 sex

2 age of respondent

Transformation None

Non-Seasonal Differencing 0

Seasonal Differencing 0

Length of Seasonal Period No periodicity

Standardization Not applied

Distribution Type Normal

Location estimated

Scale estimated

Fractional Rank Estimation Method Blom's

Rank Assigned to Ties Mean rank of tied values

Applying the model specifications from MOD_3


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Series or Sequence Length 50 50

Number of Missing Values in the

Plot

User-Missing 0 0

System-Missing 0 0


Estimated Distribution Parameters


Normal Distribution Location 1.28 2.76

Scale .454 .625


Sex


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This Q Q plot shows that the data is not normal and it has positive curve


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Age of respondent


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This QQ plot shows that data is almost normal and it has positive curve


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Graph

Notes


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Syntax GRAPH

/BAR(SIMPLE)=COUNT BY sex.


Elapsed Time 00 00:00:00.468


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Male are more then females

Notes


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Syntax GRAPH

/BAR(SIMPLE)=COUNT BY sex.


Elapsed Time 00 00:00:00.467

GRAPH

/BAR(SIMPLE)=COUNT BY age.

Graph

Notes


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Syntax GRAPH

/BAR(SIMPLE)=COUNT BY age.


Elapsed Time 00 00:00:00.685


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In this graph shows that 21-23 respondent are more then others


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Graph

Notes


Comments


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Syntax GRAPH

/BAR(SIMPLE)=VALUE(sex).


Elapsed Time 00 00:00:00.468

This graph shows that most of values falls in 1.0 and others 2.0


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Notes


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Syntax GRAPH

/BAR(SIMPLE)=VALUE(age) BY sex.


Elapsed Time 00 00:00:00.516

Graph

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Syntax GRAPH

/BAR(SIMPLE)=VALUE(age).



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Notes


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Syntax GRAPH

/BAR(SIMPLE)=VALUE(age).


Elapsed Time 00 00:00:00.516


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This graph shows that most of age respondent are falls in 21-23

Graph

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Syntax GRAPH

/BAR(SIMPLE)=VALUE(sex) BY

educationalit.


Elapsed Time 00 00:00:00.500

This graph shows 1 stand for male nd 2 stand for female most of the students are it realated to yes

Graph


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Notes


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Syntax GRAPH

/PIE=COUNT BY sex.


Elapsed Time 00 00:00:00.624


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This graph shows male are more then females

Graph

Notes


Comments


Active Dataset DataSet1Filter


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Weight

Split File


Syntax GRAPH

/PIE=COUNT BY age.


Elapsed Time 00 00:00:00.485

This graph shows 21-23 age of respondent are more then others


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Graph

Notes


Comments



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Syntax GRAPH

/PIE=SUM(sex) SUM(age)

/MISSING=LISTWISE.


Elapsed Time 00 00:00:00.469


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This graph shows sex in blue and age of respondent in green

Graph

Notes


Comments

Input Data C:\Users\Farrukh\Documents\Untitled1.savActive Dataset DataSet1


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Filter

Weight

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Syntax GRAPH

/PIE=SUM(sex) SUM(age)

SUM(educationalit) SUM(basicneed)

/MISSING=LISTWISE.


Elapsed Time 00 00:00:00.469

This graph shows that males are more age of respondent are falls in 21-23 and mostly related to education


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Graph

Notes


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Syntax GRAPH

/PIE=VALUE(sex).


Elapsed Time 00 00:00:00.577


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This graph show there are 50 entries belong to different colours

Graph

Notes


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Filter


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Weight

Split File


Syntax GRAPH

/PIE=VALUE(age).


Elapsed Time 00 00:00:00.468

This graph show there are 50 entries belong to different colours


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Graph

Notes


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Syntax GRAPH

/PIE=VALUE(sex) BY age.


Elapsed Time 00 00:00:00.483


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This graph shows most of the entries are fall between 21-23

Explore

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Missing Value Handling Definition of Missing User-defined missing values for dependent

variables are treated as missing.

Cases Used Statistics are based on cases with no missing

values for any dependent variable or factor

used.

Syntax EXAMINE VARIABLES=sex BY age

/PLOT=BOXPLOT

/STATISTICS=NONE

/NOTOTAL.


Elapsed Time 00 00:00:00.483

Warnings

sex is constant when age of respondent = less dn 17. It will be included in any boxplots produced but

other output will be omitted.

sex is constant when age of respondent = 24-26. It will be included in any boxplots produced but other

output will be omitted.

age of respondent


age of respondent

Cases

Valid Missing Total

N Percent N Percent N Percent

sex less dn 17 1 100.0% 0 .0% 1 100.0%

18-20 14 100.0% 0 .0% 14 100.0%

21-23 31 100.0% 0 .0% 31 100.0%

24-26 4 100.0% 0 .0% 4 100.0%


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sex

Explore


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Notes


Comments



Filter

Weight

Split File


Missing Value Handling Definition of Missing User-defined missing values for dependentvariables are treated as missing.



used.

Syntax EXAMINE VARIABLES=sex BY age

/PLOT=BOXPLOT

/STATISTICS=NONE

/NOTOTAL

/ID=educationalit.


Elapsed Time 00 00:00:00.531

age of respondent


age of respondent

Cases

Valid Missing Total



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sex less dn 17 1 100.0% 0 .0% 1 100.0%

18-20 14 100.0% 0 .0% 14 100.0%

21-23 31 100.0% 0 .0% 31 100.0%

24-26 4 100.0% 0 .0% 4 100.0%

sex


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Explore

Notes


Comments



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used.

Syntax EXAMINE VARIABLES=sex age

/COMPARE VARIABLE

/PLOT=BOXPLOT

/STATISTICS=NONE

/NOTOTAL/MISSING=LISTWISE.


Elapsed Time 00 00:00:00.485


Cases

Valid Missing Total


sex 50 100.0% 0 .0% 50 100.0%


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age of respondent 50 100.0% 0 .0% 50 100.0%

Explore

Notes


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Comments



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Weight

Split File






used.

Syntax EXAMINE VARIABLES=sex BY age BY

educationalit

/PLOT=BOXPLOT

/STATISTICS=NONE

/NOTOTAL.


Elapsed Time 00 00:00:00.500

Warnings

sex is constant when age of respondent = less dn 17, educational it related = yes. It will be included in

any boxplots produced but other output will be omitted.

sex is constant when age of respondent = 18-20, educational it related = 4. It will be included in any

boxplots produced but other output will be omitted.

sex is constant when age of respondent = 21-23, educational it related = 4. It will be included in any


sex is constant when age of respondent = 24-26, educational it related = yes. It will be included in any


sex is constant when age of respondent = 24-26, educational it related = no. It will be included in any



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age of respondent*educational it related


age of respondent educational it related

Cases

Valid Missing Total


sex less dn 17 Yes 1 100.0% 0 .0% 1 100.0%

18-20 Yes 7 100.0% 0 .0% 7 100.0%

No 6 100.0% 0 .0% 6 100.0%

4 1 100.0% 0 .0% 1 100.0%

21-23 Yes 13 100.0% 0 .0% 13 100.0%

No 17 100.0% 0 .0% 17 100.0%

4 1 100.0% 0 .0% 1 100.0%

24-26 Yes 1 100.0% 0 .0% 1 100.0%

No 3 100.0% 0 .0% 3 100.0%

sex


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Graph

Notes

Output Created 16-Dec-201100:23:05


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Output Created 16 Dec 2011 00:23:05

Comments



Filter

Weight

Split File


Syntax GRAPH

/HISTOGRAM=sex.


Elapsed Time 00 00:00:00.500


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Graph

Notes


Comments



Filter

Weight


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Split File


Syntax GRAPH

/HISTOGRAM=age.


Elapsed Time 00 00:00:00.468


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Graph

Notes


Comments


Active Dataset DataSet1Filter

Weight

Split File


Syntax GRAPH

/HISTOGRAM=educationalit.


Elapsed Time 00 00:00:00.453


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Conclusion

I conduct a survey on cell phone in this survey I came to know that cell phone is a basic need of every one, different peo ple use different cell phone

Most of them use Nokia cell phone and they also prefer this brand to others, the requirement of the cell phone is according to their needs, those

People who use cell phone mostly people like smart phone and touch phone , youngsters do like texting more then calls and they enjoy to use internet from their cell

Phone. the internet wap they use is face book youngsters like and use this internet wap, this survey acknowledge me alots of thing about Nokia cell phone their

Prices are very reasonable and their battery timing are also good or long time as compare to others cell phone brand like Samsung, apple etc .