The correlation between mercury concentrations‚ weight and length in various fish species are indicated in figures 4.20-21. Total mercury concentrations were determined in some fish species in both the dry and the wet season from the Weija dam. About 42 samples of fish which consisted of three (3) species were sampled in all. Among the species were tilapia zilli (n = 7). Tilapia mariae (n = 7) and Chrysichthys nigrodigitatus (n=7) all of which are consumable (edible) by human. The mean T-Hg concentration
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Scores obtained 48 39 76 68 69 56 74 58 65 73 by B If the consistency of performance is the criterion for awarding a prize‚ which student should get the prize? Use coefficient of variation to measure the consistency. Answer-------- student B should get the prize. COV of A = 28.88% COV of B=18.42% Scores of B is more consistent. Q3. Find the mean and median for the foll . data Class
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Chapter 13 Linear Regression and Correlation True/False 1. If a scatter diagram shows very little scatter about a straight line drawn through the plots‚ it indicates a rather weak correlation. Answer: False Difficulty: Easy Goal: 1 2. A scatter diagram is a chart that portrays the correlation between a dependent variable and an independent variable. Answer: True Difficulty: Easy Goal: 1 AACSB: AS 3. An economist is interested in predicting
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through a heat transfer coefficient. Heat is generated in the slab at the rate of 1.0 kW/m3. The thermal conductivity of the slab is 0.2 W/m-K. (a) Solve for the temperature distribution in the slab‚ noting any assumptions you must make. Be careful to clearly identify the boundary conditions. (b) Evaluate T at the front and back faces of the slab. (c) Show that your solution gives the expected heat fluxes at the back and front faces. Q.2 Compute overall heat transfer coefficient U for the slab shown
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To make cost estimates‚ project managers use cost analysis; a discipline that attempts to forecast the ultimate cost of a project. The difficulty about this analysis‚ especially for complex projects‚ is that there are a lot of uncertainties about cost items such as technology‚ productivity of human resources‚ economic conditions‚ market conditions‚ prices‚ inflation and other future risks and events. In general uncertainty occurs for a number of reasons: • Uniqueness (no similar experience) ⁎ Corresponding
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Correlation coefficients measure the strength of association between two variables. The most common correlation coefficient‚ called the Pearson product-moment correlation coefficient‚ measures the strength of the linear association between variables. In this tutorial‚ when we speak simply of a correlation coefficient‚ we are referring to the Pearson product-moment correlation. Generally‚ the correlation coefficient of a sample is denoted by r‚ and the correlation coefficient of a population is
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of Linear Correlation Pearson’s Correlation Coefficient (r) Pearson’s R measures the strength or degree of association between two interval ratio variables ranging from .0 to 1 either positive or negative. It is the square root of correlation determination. The closer the measure is to 1 or -1‚ the stronger the relationship. Thus‚ 80 or 90 in either direction indicates a strong relationship exists. Zero means there is no correlation. Pearson’s R is the most commonly used correlation measure. It
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Table 1; Table 2; Table 2; Table 3; Table 3; Correlation coefficient formula; Table 1; correlation coefficient = 0.396078212 Table 2; correlation coefficient = 0.601557088 Table 3; correlation coefficient = 0.509917729 Working out; 6) Use your results to assess whether combined data from the whole class matches the “ideals” of the Vitruvian man more closely than measurements based entirely on yourself. When assessing the combined results‚ to that of the results
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Iran". Methodology: Descriptive-correlation method was used in this survey and the statistical population included employees of Customs headquarters equal to six-hundred seventy eight (678) persons. Sample volume was selected through random class sampling method that was equal to two-hundred fifty (250) persons. Questionnaire was used to collect the required data and data analysis was accomplished using inferential statistics tests such as Pierson correlation coefficient and step by step regression analysis
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Titli Declaration I have declare that the report work ‘’Analysis of customer satisfaction of BERGER PAINTS BANGLADESH LIMITED’’ submitted to ASA UNIVERSITY BANGLADESH as apart of the BBA curriculam‚ is a record of an original work done by me under the guidance of prof Jesmin Akter Assistant Professor Department of Business Administration ASA University‚ Bangladesh. Table of Contents SERIAL NO. PARTICULARS PAGE NO 01
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