on sectoral (agriculture‚ industry and service) growth patterns. It analyses data from secondary sources and estimates the relationship between inflow of FDI and annual output growth achieved in different sectors between 1995-2005‚ by computing correlation co-efficient and corresponding p-values. The analyses reveal that FDI inflow in the industrial sector does not appear to correlate much with industrial
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conclude that‚ as the size of the home (reported below in thousands of square feet) increases‚ the selling price (reported in $ thousands) also increases? * Compute the coefficient of correlation. * = [12(1344) – (13.8)(1160)]/12(16.26) – (13.8)2][12(114850) – (1160)2]=0.30722 * Determine the coefficient of determination * r2 = 256.4103/2716.667=0.09438 * df = 12 -2 = 10 * table b2 t = 1.812; Reject the H0 if t > 1.812 * t = r ((n – 2)1/2) / (1 –
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three figures all seem to follow similar stochastic trends with price series that do not drift too far apart for each market pair indicating price co-movement. Indeed‚ the bivariate correlation coefficient included in Table 7 in the appendix shows that the price series are highly correlated and that the correlation is invariant to distance. In addition‚ observed price Spikes are common to all markets and can be observed around the years 2001‚ 2005‚ 2008 and 2014. Droughts in 2001 and 2005 explain
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Chapter 13 Problems (2‚ 9‚ 11‚ & 14) 2) Determine the coefficient of correlation and the coefficient of determination. Interpret the association between X and Y. X Y x^2 xy 5 13 25 65 3 15 9 45 6 7 36 42 3 12 9 36 4 13 16 52 4 11 16 44 6 9 36 54 8 5 64 40 39 85 211 378 r = (378) - (39)(85) / 8 = -36.375 √[211 - (39)^2 / 8] *
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A) $69‚200 B) $42‚526.70 C) $26.7 D) $69.20 A6. Explain what the following sample correlation coefficients tell you about the relationship between the x and y values in the sample: r = - 0.8 A) No correlation. B) Perfect negative correlation. C) Strong negative correlation. D) Weak negative correlation. A7. What is meant by time-series data? (A) A set of values which occurs sequentially in time. (B) A set
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BU1007 Business Data Analysis and Interpretation Singapore Campus‚ Study Period SP53‚ 2013 Statistical Report Analysis of Case study 3: Heavenly Chocolates website transactions Prepared for Dr Tjong Budisantoso Done by Mr. Keung‚ Tseung Student ID : 12776910 20/12/2013 Table of contents Introduction ---------------------------------------------------------------------------
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will affect their job outcomes. For this purpose‚ four banks: SCB‚ RBS‚ MCB and UBL were chosen‚ taking 25 employees from each and collecting data through a structured questionnaire. For testing hypotheses the Correlation Model was used to identify the influenced factors based on the correlation value which is significant at the 0.05 level. The study found significant relationship between the independent variable i.e. Succession Planning and dependent variable i.e. Employee Retention. Therefore the
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Correlation and Regression Analysis : Comparison between Gold rates and Sensex Correlation : Correlation is a statistical technique that can show whether and how strongly pairs of variables are related. Correlation is computed into what is known as the correlation coefficient‚ which ranges between -1 and +1. Perfect positive correlation (a correlation co-efficient of +1) implies that as one security moves‚ either up or down‚ the other security will move in lockstep‚ in the same direction
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......................................................................... 3 Core – Scattergraph Draw & Interpret (Step 2 Continued) .............................................................................................. 4 Core – Correlation Coefficients (Step 3) ........................................................................................................................... 5 Core – Regression Equation (Step 4)..................................................................
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Tutorial 11 A11.1 Data on manatee deaths due to powerboats was used to construct a linear regression model relating these deaths to the number of registered powerboats. Year 1977 1978 1979 1980 1981 1982 1983 Power boats (thousands) 447 460 481 498 513 512 526 Manatee Deaths 13 21 24 16 24 20 15 Year 1984 1985 1986 1987 1988 1989 1990 Power boats (thousands) 559 585 614 645 675 711 719 Manatee Deaths 34 33 33 39 43 50 47 The
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