Body - Traffic Jam

Topics: Sampling, Data analysis, Causality Pages: 6 (1296 words) Published: December 1, 2012
Chapter 1: Introduction

1.1Origin of the report
This report has been prepared following the instruction of our course teacher Pro. Ali Akkas as a part of our course “Business Communication” under the EMBA program of Dhaka University.

1.2 Objective of the report
1. Broad objective
To discuss traffic jam, it’s causes and remedies

2. Specific objective
-To discuss the effects of traffic jam on environment and social life, -To be introduced with the way of relief from traffic jam. - To find the way of upgrading the traffic systems

1.3 Scope and Limitations of the report

This report could have even more wealth and information. But, due to limited time, few information could be collected. More budgeting on this report could have given it a aristocratic look. In spite of these limitations, it has been tried to enrich this report by proper and authentic information.

It has been tried to be rational with the real figure of traffic jam. It is believed that this report will help the follower to go for further analysis. Chapter 02: Methodology

2.1 Population Parameters

A parameter is a numerical summary of a population; because populations have so many members, these can never be known except if a census is taken.

2.2 Sampling Design
In the theory of finite population sampling a sampling design specifies for every possible sample its probability of being drawn. Mathematically a sampling design is denoted by the function P(S) which gives the probability of drawing a sample. 2.3 Variables Covered

Here we have included
-urban traffic problems
-suburban traffic problems
-high way traffic problems

2.4 Methods of Data Collection
There are four main methods of data collection.
• Census. A census is a study that obtains data from every member of a population. In most studies, a census is not practical, because of the cost and/or time required.

• Sample survey. A sample survey is a study that obtains data from a subset of a population, in order to estimate population attributes.

• Experiment. An experiment is a controlled study in which the researcher attempts to understand cause-and-effect relationships. The study is "controlled" in the sense that the researcher controls (1) how subjects are assigned to groups and (2) which treatments each group receives.

• Observational study. Like experiments, observational studies attempt to understand cause-and-effect relationships. However, unlike experiments, the researcher is not able to control (1) how subjects are assigned to groups and/or (2) which treatments each group receives.

2.5 Data Analysis Plan

The appropriate methods of data analysis are determined by data types and variables of interest, the actual distribution of the variables, and the number of cases. Different analyses of the same data set may reflect or represent different aspects of the underlying data structure. Once a plan has been established, it could contain any combination of the following types of data analysis strategies:

• Exploratory: This type of data analysis often occurs when a program is new, and it is unclear what to expect from the data.

• Descriptive: The most common type of data analysis, this approach will summarize your findings and describe the sample.

• Inferential: Inferential statistics allow us to draw conclusions about the larger population from which the sample is drawn. These powerful techniques may be able demonstrate if a change has occurred as a result of your program. PDA's Statistics Division specializes in many sophisticated data analysis techniques.

Chapter 3: Traffic Jam, It’s Causes, Effects and Remedies
3.1 Causes of Traffic Jam
“During experiment, it has been found that human error is a major cause of most frustrating kinds of traffic jams”. ( Annexes – I) In generally the traffic jams...
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