PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT Definition It is the measure of the linear correlation between two variables X and Y It is the measure of the strength of a linear association between two variables and is denoted by r. It tells you how strong the linear correlation is for paired numeric data e.g. height and weight. The Pearson correlation coefficient‚ r‚ indicates how far away all these data points are to this line of best fit. Development It was the imagination and idea of Sir Francis
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Elementary Concepts in Statistics Overview of Elementary Concepts in Statistics. In this introduction‚ we will briefly discuss those elementary statistical concepts that provide the necessary foundations for more specialized expertise in any area of statistical data analysis. The selected topics illustrate the basic assumptions of most statistical methods and/or have been demonstrated in research to be necessary components of one’s general understanding of the "quantitative nature" of reality
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Master of Business Administration – MBA Semester I Subject code – MB0040 Subject Name – Statistics For Management Assignment Set – 1 Q.1. Why it is necessary to summarise date? Explain the approaches available to summarize the data distributions? Q.2. Explain the purpose of tabular presentation of statistical data. Draft a form of tabulation t show the distribution of population according to i) Community by age‚ ii) Literacy‚ iii) Sex‚ and iv) Marital status. Q.3. Give a brief note of the
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I. INTRODUCTION A. Statement of the problem What are the common problems encountered by different small business enterprises? B. Importance of the study By determining the common problems or difficult situations encountered by different small business enterprises‚ we can also determine the possible solutions or alternative in solving such business problem and to find or create actions to prevent in copping which such difficulties. Also we can take necessary actions for the problem will
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Association [ASA]‚ 2008). Statistics is a division of mathematics that centers on the collection and evaluation of data‚ which can be drawn upon to make conclusions (Aron‚ Aron‚ & Coups‚ 2006‚ 2). Two branches of statistics exist‚ including descriptive and inferential domains. Extrapolation beyond the data is where the real difference emerges. Indeed‚ these two subcategories vary in function and definition. However‚ a relationship exists between descriptive and inferential statistics‚ irrespective of the
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Biodiversity of the Indian Desert and it´s Value Amit Kotia and Ashwani Kumar Biotechnology Lab‚ Department of Botany University of Rajasthan‚ Jaipur – 302004 INDIA Abstract The state of Rajasthan is situated between 23º3’ and 30º12’ N latitude and 69º30’ and 78º17’ E longitude . The total land area of the state is about 3‚24‚239 km² ‚ out of which about 1‚98‚100 km² is arid and the rest semi arid. The physical features are characterized mainly by the Aravallis and to the some extent by
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Showing the detailed equations and calculations‚ compute the: • Population Mean • Population Median Median is 4310 because it is the midpoint of the values. There are 5values. Therefore‚ 3rd value is the median. • Population Mode There is no mode because there is no value of the observation that appears most frequently. Every value appears only once. • Mean Deviation • Coefficient of the Mean Deviation (it is the Mean Deviation divided by the Mean) • Population
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1.1 Outline the health and safety policies and procedures of the work setting Health and safety legislations and policy aim to make sure that the workers‚ children‚ young people and families are safe and protected from harm when at work or using different services. You do not need to be an expert in this area‚ but you will need to be aware of the legal issues and national and local guidance which relates to health and safety and also to know where to go and who you should ask when you need advice
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P ( T ∩ R ) = P ( T ) . P ( R ) 0.26 0.23 0.26 0.23 0.49 0.49 0.49 0.49 0.26 0.49 0.26 0.49 0.49 0.23 0.49 0.23 0.26 0.26 0.23 0.23 P ( T ∩ R ) = P ( T ) . P ( R ) • • • events P ( T ) . P ( R ) are indepentdent (iii) Refer
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