Large cities of the world, including country names

  • 作成日:2013年12月31日 最終更新日:2013年12月31日
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提出者情報

データジャケットの題名 Large cities of the world, including country names
データの所在・所有者 http://geography.uoregon.edu/geogr/data/csv/cities2.csv
データ収集方法やコスト The dataset were collected by department of geography, university of Oregon. The method used was from several ways such as public survey and some information drawn from international organizations like the World Bank. The cost incurred during process of data collection is not provided.
データの共有について その他
データの共有について (その他を選ばれた方)

データの分析・シミュレーションについて

データの種類 テキスト 数値 時系列
データの変数(パラメーター)の変数名 AREA|CITY|GROWTH RATE|WATER ACCESS|FOOD SUPPLY|POPULATION IN 80 90 00|NUMBER OF VEHICLES OWNED|PHONE ACCESS|ELECTRICITY ACCESS|COUNTRY
データの概要説明 The dataset provide information about the number of population, growth rate, food supply, utilities access and etc. of the most largest cities in the world.
想定しているデータの分析・シミュレーションプロセス Since the data is time series and involves many variables with the one we are interested is the number of population. Ordinary least square method can be applied to analyze the dataset. The process begins with selection of dependent and independent variables and put them into a regression form. Then, the commercial package like Excel can be used to find the value of each coefficient, completing the model. Some assumptions will be raised such as all dependent variables are unbiased variables and there are no missing significant variables in the equation. The derived equation can be tested using past dataset to estimate its robustness.
想定しているデータの分析・シミュレーションプロセスの結果 (データ分析結果/ツールの出力/典型例など) The derived equation can be used to predict the growth rate of a city. If we assume the value of dependent variables, we can observe the number of population, and can see how each variable influences the outcome. Moreover, we can apply further by switching the independent variable among other dependent variables, or even introduce a new variable to the model.
上記の分析・シミュレーションプロセス以外に期待する分析 We anticipate that the model can be adjusted to be more precise and eventually lead to some advisable information that may prove useful for those people who make the policy.

その他

自由記述 The dataset is a valuable source that provides the information related to the matter concerned. The selection of methods used to analyze the dataset is a very important step as different methods lead to different interpretations. Thus, we must carefully combine the dataset with a proper method to obtain the most favorable result.
入手したいデータ/ツール A computer software with robust computing functions that is user-friendly and flexible enough for users to design the dataset according to their preferences.
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