business research and methods

8/14/2019 Business Research and Methods

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Prof. Dawod Ilyas Butt


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Reasons of road accidents : A case study of Lahor


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Muhammad Umer NaeemI.D. 074132-019

Furqan Saleem

I.D 060234-036 Asif Rafique Bhatti

I.D. 084232-044

Saleem ShahzadI.D. 074132-033


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The past few years show that increase in the road

accidents giving a red signal for public safety on road.

Past 5 years there is an alarming increase in the

accidents. play our role in the investigation of the reasons and

factors that causes the road accidents in terms to secure

the public safety.


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Causes of bike and car accidents in urbanareas: A case study of Lahore.


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To understand the factors that causes accidents.

To determine the main factors that provokes fast

driving.

To understand the after effects of road accidents in the

public.


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Sample Design

The data will be collected from males and

female individuals (sampling elements). Theprocess involves the following steps:

Target Population

The target population includes people livingin urban areas of Lahore; the data include

people living in specific areas i.e.Drivers of bikes and cars


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Tools

SPSS

Limitation

o Urban areas of Lahoreo Drivers of Cars and bikeso Females between the age of 21 to 35


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Age Intention during drive

Male, Female Weather

Skill Level Use of seat belts

Vehicle condition Side mirror

Mode of driving Traffic rules

Attitude problem Drive for need or drive forenjoyment


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i) Fun in Driving and Gender:

First of all we see that if there is any relationship

between gender and fun in driving. For this purpose we

will make hypotheses and then run cross tabs in the

SPSS on the collected data.

Ho = There is no significant relationship between

gender and fun in driving

H1 = There is significant relationship betweengender and fun in driving


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Chi-Square Tests

Value df Asymp. Sig.(2-sided)

Pearson Chi-Square

2.739a 4 .602

Likelihood Ratio4.251 4 .373

N of ValidCases

55


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We see that if there is any relationship between fun in

driving and different levels of age. For this purpose we



Ho= There is no significant relationship between fun

in driving and Age levels

H1 = There is significant relationship between fun indriving and Age levels


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Chi-Square Tests

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 25.492a 12 .013

Likelihood Ratio 31.403 12 .002

Linear-by-Linear Association 6.436 1 .011

N of Valid Cases 55

From the above chi-square test we can see that chi-square significance

value (p-value) is less than alpha (0.10) so we have sufficient evidenceto reject Ho and we will accept H1; that there is a significant

relationship between fun in driving and Age levels and we are 90%sure about it.


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We see that if there is any relationship between safety

measure and frequent accidents. For this purpose we



Ho= There is no significant relationship between

safety measure and frequent accidents

H1 = There is significant relationship between safetymeasure and frequent accidents


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Chi-Square Tests





N of Valid Cases 55


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We see that if there is any relationship between fastspeed and frequent accidents. For this purpose we will

make hypotheses and then run cross tabs in the SPSS

on the collected data.


fast speed and frequent accidents

H1= There is significant relationship between fast

speed and frequent accidents


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Chi-Square Tests




Linear-by-Linear Association .173 1 .677

N of Valid Cases 55

From the above chi-square test we can see that chi-square significance value (p-value) is not

less than alpha (0.10) so we have not sufficient evidence to reject Ho at 90% level ofconfidence. This implies that there is no as such significant relationship between fast speed

and frequent accidents.


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We see that if there is any relationship betweenawareness of traffic rules and frequent accidents. Forthis purpose we will make hypotheses and then run crosstabs in the SPSS on the collected data.

Ho = There is no significant relationship between

awareness of traffic rules and frequent accidents

H1 = There is significant relationship between

awareness of traffic rules and frequent accidents


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Chi-Square Tests





N of Valid Cases 55

From the above chi-square test we can see that chi-square significance value (p-value)

is not less than alpha (0.10) so we have not sufficient evidence to reject Ho at 90% level

of confidence. This implies that there is no as such significant relationship betweenawareness of traffic rules and frequent accidents.


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We see that if there is any relationship between awarenessof traffic rules and obedience of traffic rules. For this

purpose we will make hypotheses and then run cross tabs in

the SPSS on the collected data.

H

o= There is no significant relationship between

awareness of traffic rules and obedience of traffic rules

H1= There is significant relationship between awareness

of traffic rules and obedience of traffic rules


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Chi-Square Tests





N of Valid Cases 55

From the above chi-square test we can see that chi-square significance value (p-value) is less

than alpha (0.10) so we have sufficient evidence to reject Ho and we will accept H1;

that there

is a significant relationship between awareness of traffic rules and obedience of traffic rules

and we are 90% sure about it.


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Chi-Square Tests





N of Valid Cases 55

From the above chi-square test we can see that chi-square significance value (p-value) is not

less than alpha (0.10) so we have not sufficient evidence to reject Ho at 90% level of

confidence. This implies that there is no significant relationship between accidents caused byrespondents and violation of traffic rules.


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We see that if there is any relationship betweenaccidents caused byothers and high beam lights. For

this purpose we will make hypotheses and then run

cross tabs in the SPSS on the collected data.


accidents caused by others and high beam lights

H1 = There is significant relationship betweenaccidents caused by others and high beam lights


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Chi-Square Tests





N of Valid Cases 55

From the above chi-square test we can see that chi-square significance value (p-value) is

less than alpha (0.10) so we have sufficient evidence to reject Ho and we will accept H1;

that there is a significant relationship between accidents caused byothers and usage of highbeam lights and we are 90% sure about it.


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We see that if there is any relationship between accidents causedby respondent and driving under influence of medicine. For this

purpose we will make hypotheses and then run cross tabs in the


Ho = There is no significant relationship between accidentscaused by respondent and driving under influence of medicine

H1 = There is significant relationship between accidents caused

by respondent and driving under influence of medicine


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Chi-Square Tests





N of Valid Cases 55

From the above chi-square test we can see that chi-square significance value (p-value) is not less than

alpha (0.10) so we have not sufficient evidence to reject Ho at 90% level of confidence. This implies that

there is no significant relationship between accidents caused by respondent and driving under the

influence of medicine.


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viewing billboards. For this purpose we will make hypothesesand then run cross tabs in the SPSS on the collected data.

Ho = There is no significant relationship between accidents

caused by respondent and viewing billboards

H1 = There is significant relationship between accidents

caused by respondent and viewing billboards


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Chi-Square Tests





N of Valid Cases 55


not less than alpha (0.10) so we have not sufficient evidence to reject Ho at 90% level

of confidence. This implies that there is no significant relationship between accidentscaused by respondent and viewing billboards


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We see that if there is any relationship between accidentscaused by respondent and listening high volume music. Forthis purpose we will make hypotheses and then run crosstabs in the SPSS on the collected data.

Ho = There is no significant relationship betweenaccidents caused by respondent and listening highvolume music

H1 = There is significant relationship between accidents

caused by respondent and listening high volume music


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Chi-Square Tests





N of Valid Cases 55


not less than alpha (0.10) so we have not sufficient evidence to reject Ho at 90% level of

confidence. This implies that there is no significant relationship between accidentscaused by respondent and listening high volume music.


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