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This e-book aims to present the most critical aspects of knowledge about using experiments in economics and practical tools for using them. The topic is extended to the more advanced and increasing in popularity area of biometric research. The book is divided into three parts mirroring experimentation. The first part provides theoretical background and tips about organising own research. The chapter is concluded with a guide focused on writing a research report in APA style. This part includes an example of the actual research report. The next part has two chapters, and both are guided tours allowing to plan and conduct eye-tracking research and electrodermal activity research (EDA). The chapters contain details about preparing experiments, conducting them, using the dedicated software to analyse collected data and interpreting the default charts. The last part is devoted to the data analysis and is universal, goes beyond the biometric experiments. There are three chapters in this part covering the standard procedures used in the analysis of experiments. The first part includes tests for one hypothesis: parametric t-test and One-Way ANOVA and non-parametric siblings: Mann Whitney U test and Kruskal-Wallis test. The next part describes tests allowing testing more hypotheses: ANOVA without repetition and ANOVA with repetitions. Furthermore, the last chapter deals with dependent samples, which are a popular approach in experiments. This part describes the dependent sample t-test and Wilcoxon test. The effect sizes calculations are included; each test is shown with screenshots from SPSS and some additional screenshots from Excel. This approach allows following the procedure step by step. The examples help easily understand procedures and interpretations; they were chosen from areas of sustainability and innovations to match the general idea of the e-books series prepared within the CENETSIE program. The book contains texts that can be useful in the teaching process. It can be helpful in graduate programs in economics and business schools. Programs of doctoral schools cab benefit from this book as well.

Biometry --- Demography. --- Research.

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Biometry --- Biometry. --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Statistical methods --- Biomathematics --- Statistics

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Biomathematics. Biometry. Biostatistics --- Biometry --- Biométrie --- 57.087.1 --- Biometry. --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistics --- Biometry. Statistical study and treatment of biological data --- Statistical methods --- 57.087.1 Biometry. Statistical study and treatment of biological data --- Biométrie

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The third edition of this innovative work again provides a unique perspective on the clinical discovery process by providing input from experts within the NIH on the principles and practice of clinical research. Molecular medicine, genomics, and proteomics have opened vast opportunities for translation of basic science observations to the bedside through clinical research. As an introductory reference it gives clinical investigators in all fields an awareness of the tools required to ensure research protocols are well designed and comply with the rigorous regulatory requirements necessary to m

Biomathematics. Biometry. Biostatistics --- Human medicine --- Clinical medicine --- Research.

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This book covers methods of applied statistics for researchers who design and conduct experiments, perform statistical inference, and write technical reports. These research activities rely on an adequate knowledge of applied statistics. The reader both builds on basic statistics skills and learns to apply it to applicable scenarios without over-emphasis on the technical aspects. Demonstrations are a very important part of this text. Mathematical expressions are exhibited only if they are defined or intuitively comprehensible. This text may be used as a guidebook for applied researchers or as an introductory statistical methods textbook for students, not majoring in statistics. Discussion includes essential probability models, inference of means, proportions, correlations and regressions, methods for censored survival time data analysis, and sample size determination.

Biometry. --- Statistics. --- Biostatistics. --- Statistical Theory and Methods. --- Research --- Statistical methods.