More Data or Better Data? A Statistical Decision Problem

2017 ◽  
Vol 84 (4) ◽  
pp. 1583-1605 ◽  
Author(s):  
Jeff Dominitz ◽  
Charles F. Manski
Keyword(s):  
Data Collection ◽  
Decision Problem ◽  
Low Cost ◽  
Statistical Decision Theory ◽  
Sample Design ◽  
Statistical Decision ◽  
Finite Samples ◽  
Statistical Decision Problem ◽  
Sample Member

AbstractWhen designing data collection, crucial questions arise regarding how much data to collect and how much effort to expend to enhance the quality of the collected data. To make choice of sample design a coherent subject of study, it is desirable to specify an explicit decision problem. We use the Wald framework of statistical decision theory to study allocation of a budget between two or more sampling processes. These processes all draw random samples from a population of interest and aim to collect data that are informative about the sample realizations of an outcome. They differ in the cost of data collection and the quality of the data obtained. One may incur lower cost per sample member but yield lower data quality than another. Increasing the allocation of budget to a low-cost process yields more data, while increasing the allocation to a high-cost process yields better data. We initially view the concept of “better data” abstractly and then fix attention on two important cases. In both cases, a high-cost sampling process accurately measures the outcome of each sample member. The cases differ in the data yielded by a low-cost process. In one, the low-cost process has non-response and in the other it provides a low-resolution interval measure of each sample member’s outcome. In these settings, we study minimax-regret sample design for prediction of a real-valued outcome under square loss; that is, design which minimizes maximum mean square error. The analysis imposes no assumptions that restrict the unobserved outcomes. Hence, the decision maker must cope with both the statistical imprecision of finite samples and the partial identification of the true state of nature.

scholarly journals Analisis Pengaruh Brand Image, Harga, Dan Kualitas Produk Terhadap Keputusan Pembelian Mobil (Studi Kasus Mobil LCGC di Surakarta)

2017 ◽  
Vol 12 (1) ◽  
Author(s):  
Budi Istiyanto, Lailatan Nugroho
Keyword(s):  
Data Collection ◽  
Multiple Regression ◽  
Brand Image ◽  
Low Cost ◽  
Purchase Decision ◽  
Purchasing Decisions ◽  
Quality Product ◽  
Quality Of Products

AbstractThis study aimed to determine the effect of variable brand image, price, quality of product to decision of purchasing a car LCGC (Low Cost Green Car), either partial or jointly and to find among variables brand image, price, and quality of products which are larger role in influencing purchasing decisions LCGC car. Data collection techniques researchers did by observation and questionnaires directly by visiting the object of the research is to consumers who have made a purchase decision, especially type Agya LCGC car, AYLA, and Karimun Wagon R in Surakarta which would then be sampled. The data have been collected and tabulated and analyzed using multiple regression analysis.The results showed that the variables that significantly affect purchasing decisions is price and quality of products. While the variable Brand Image does not affect significantly. While the variables that affect predominantly variable price.Keyword: Brand Image, Price, Quality Product, Purchase Decision AbstrakPenelitian ini bertujuan untuk mengetahui pengaruh antara variable brand image, harga, dan kualitas produk terhadap keputusan pembelian mobil LCGC (Low Cost Green Car) baik secara partial maupun secara bersama-sama dan untuk mengetahui diantara variable brand image, harga, dan kualitas produk mana yang lebih berperan dalam mempengaruhi keputusan pembelian mobil LCGC. Teknik pengumpulan data peneliti lakukan dengan cara observasi dan penyebaran kuisioner secara langsung dengan cara mendatangi obyek penelitian yaitu kepada konsumen yang telah melakukan keputusan pembelian mobil LCGC terutama type AGYA,AYLA, dan Karimun Wagon R di wilayah Surakarta yang selanjutnya akan dijadikan sampel. Data yang telah terkumpul kemudian ditabulasi dan diolah dengan menggunakan analisis regresi berganda.Hasil penelitian menunjukkan bahwa variabel yang mempengaruhi secara signifikan keputusan pembelian adalah harga dan kualitas produk. Sedangkan variabel Brand Image tidak mempengaruhi secara signifikan. Sedangkan variabel yang berpengaruh secara dominan adalah variabel harga.Kata kunci: Brand Image, Harga, Kualitas Produk, Keputusan Pembelian

A continuous time inventory model

1966 ◽  
Vol 3 (2) ◽  
pp. 538-549 ◽  
Author(s):  
J. A. Bather
Keyword(s):  
Inventory Control ◽  
Discrete Time ◽  
Optimal Policy ◽  
Continuous Time ◽  
Decision Problem ◽  
Optimization Problem ◽  
Continuous Treatment ◽  
Inventory Level ◽  
Statistical Decision ◽  
Statistical Decision Problem

This paper discusses an optimization problem arising in the theory of inventory control. Much of the previous work in this field has been focused on the Arrow-Harris-Marschak model, [1], [2], in which the inventory level can be modified only at the instants of discrete time. Here, we shall be concerned with a continuous time analogue of the model, in an attempt to avoid the difficulties experienced in solving the basic integral equations. The approach was suggested by recent investigations of a statistical decision problem, [3], [5], which exploited the advantages of a continuous treatment. Although the ideas discussed here are relatively straightforward and involve strong assumptions as to the behavior of the inventory, the explicit character of the optimal policy is encouraging and particular solutions might nevertheless provide useful restocking procedures.

The quantum monty hall problem

2002 ◽  
Vol 2 (5) ◽  
pp. 355-366
Author(s):  
G.M. D'Ariano ◽  
R.D. Gill ◽  
M. Keyl ◽  
B. Kummerer ◽  
H. Maassen ◽  
...  
Keyword(s):  
Optimal Strategy ◽  
Decision Problem ◽  
Prior Information ◽  
Classical Case ◽  
Statistical Decision ◽  
Statistical Decision Problem ◽  
Finite Set ◽  
Quantum Version ◽  
Person Game ◽  
Classical Game

We consider a quantum version of a well-known statistical decision problem, whose solution is, at first sight, counter-intuitive to many. In the quantum version a continuum of possible choices (rather than a finite set) has to be considered. It can be phrased as a two person game between a player P and a quiz master Q. Then P always has a strategy at least as good as in the classical case, while Q's best strategy results in a game having the same value as the classical game. We investigate the consequences of Q storing his information in classical or quantum ways. It turns out that Q's optimal strategy is to use a completely entangled quantum notepad, on which to encode his prior information.

A continuous time inventory model

1966 ◽  
Vol 3 (02) ◽  
pp. 538-549 ◽  
Author(s):  
J. A. Bather
Keyword(s):  
Inventory Control ◽  
Discrete Time ◽  
Optimal Policy ◽  
Continuous Time ◽  
Decision Problem ◽  
Optimization Problem ◽  
Continuous Treatment ◽  
Inventory Level ◽  
Statistical Decision ◽  
Statistical Decision Problem

This paper discusses an optimization problem arising in the theory of inventory control. Much of the previous work in this field has been focused on the Arrow-Harris-Marschak model, [1], [2], in which the inventory level can be modified only at the instants of discrete time. Here, we shall be concerned with a continuous time analogue of the model, in an attempt to avoid the difficulties experienced in solving the basic integral equations. The approach was suggested by recent investigations of a statistical decision problem, [3], [5], which exploited the advantages of a continuous treatment. Although the ideas discussed here are relatively straightforward and involve strong assumptions as to the behavior of the inventory, the explicit character of the optimal policy is encouraging and particular solutions might nevertheless provide useful restocking procedures.

scholarly journals Ideas and Perspectives: Enhancing research and monitoring of carbon pools and land-to-atmosphere greenhouse gases exchange in developing countries

2021 ◽  
Author(s):  
Dong-Gill Kim ◽  
Ben Bond-Lamberty ◽  
Youngryel Ryu ◽  
Bumsuk Seo ◽  
Dario Papale
Keyword(s):  
Developing Countries ◽  
Data Collection ◽  
Low Cost ◽  
Climate Change Impacts ◽  
Appropriate Technology ◽  
Local Staff ◽  
Moral Importance ◽  
Data Collection And Analysis ◽  
C Cycle

Abstract. Carbon (C) and greenhouse gas (GHG) research has traditionally required data collection and analysis using advanced and often expensive instruments, complex and proprietary software, and skilled technicians. Partly as a result, relatively little C and GHG research has been conducted in resource-constrained developing countries. At the same time, these are the same countries and regions in which climate-change impacts will likely be strongest, and in which major science uncertainties are centred, given the importance of dryland and tropical systems to the global C cycle. Increasingly, scientific communities have adopted appropriate technology and approach (AT&A) for C and GHG research, which focuses on low-cost and low-technology instruments, open source software and data, and participatory and networking-based research approaches. Adopting AT&A can mean acquiring data with fewer technical constraints and lower economic burden and is thus a strategy for enhancing C and GHG research in developing countries. However, AT&A can be characterized by higher uncertainties; these can often be mitigated by carefully designing experiments, providing clear protocols for data collection, and monitoring and validating the quality of obtained data. For implementing this approach in developing countries, it is first necessary to recognize the scientific and moral importance of AT&A. At the same time, new AT&A techniques should be identified and further developed. All these processes should be promoted in collaboration with local researchers and through training local staff and encouraged for wide use and further innovation in developing countries.

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