linear regression model to explain the relationship between number of sales calls and number of units sold y=2.139x-1.760 Number of units sold=2.139Number of units sold-1.760 c) Calculate and interpret the coefficient of correlation r=0.853=0.9236 (There is strong correlation between two variables as its near 1) d) the coefficient of determination r2=0.853(The magnitude of the coefficient of determination indicates the proportion of variance in one variable‚ explained from knowledge
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Linear Regression & Best Line Analysis Linear regression is used to make predictions about a single value. Linear regression involves discovering the equation for a line that most nearly fits the given data. That linear equation is then used to predict values for the data. A popular method of using the Linear Regression is to construct Linear Regression Channel lines. Developed by Gilbert Raff‚ the channel is constructed by plotting two parallel‚ middle lines above and below a Linear Regression
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The methodology of this study is use Augmented Dickey Fuller (ADF) test statistic to determine whether the variables had been used are stationary or non-stationary. Vector Auto Regression (VAR) method is apply in this study. The advantages of VAR is time series can be exhibited at the same time. The VAR methodology is revises for autocorrelation and endogeneity parametrically using vector error correction model (VECM) specification. Base on Johansen (1988; 1995)‚ the benefit of VECM is that it prevents
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Introduction: The main idea of a multiple regression analysis is to understand the relationship between several independent variables and a single dependent variable. (Lind‚ 2004) A model of the relationship is hypothesized‚ and estimates of the parameter values are used to develop an estimated regression equation.(abyss.uoregon.edu) The multiple regression equation used to describe the relationship is: Y’ = a + b1X1 + b2X2 + b3X3 + . + bkXk. It is used to estimate Y given selected X values
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Revitalizing Dell: Forecast Dell’s 2009 and 2010 revenues • Work through the “Proposed Steps” of Case 9-1 Revitalizing Dell in your textbook – Make lagged drivers – Use correlation to pick a lagged driver – Build a linear forecast model using regression‚ perform DW test on residuals – Repeat if residuals do not pass DW test • Forecast revenues and generate 95% prediction intervals for 2009 and 2010 6 Revitalizing Dell: Bright forecast 7 Revitalizing Dell: Harsh reality 8 Revitalizing
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required to design an experiment. Experimental design has been provided for you to use instead. You are however required to submit a Risk Assessment for the investigation. Students are to work independently. However‚ you will need to collect raw data from 4 other students to make the 6 trials. The final version is to be submitted to TURNITIN and then class teacher. A journal will need to be included as part of the final submission. Time Allowed: 4 weeksDue Dates
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Earth travels at an approximate speed of 67‚000 miles an hour. While we are orbiting around the Sun‚ we are also rotating around an imaginary axis of the earth‚ with one revolution representing one day. However‚ this axis that goes through the earth from the North Pole to the South Pole is not just up and down‚ but is on a tilt of 23.5°. This tilted axis is the primary cause of the four seasons of the year - spring‚ summer‚
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AND CONs OF INCREASING OIL PRICE 1. INTRODUCTION In this decade‚ the price of oil has been raised 3 times. The era of President SBY has the record of increasing oil price (premium). The policy was made by SBY has become pro and con between the expert of economic. Some people said that increasing the oil price is just can’t be done because it’s contra with UU‚ but government said that if we don’t raise the oil price it will absorb the APBN because the import oil price is higher and higher time
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data. As evident in the table‚ the 10oC temperature is very accurate as the range was 0‚ resulting in an error percentage of 0%. However‚ the 35oC temperature had a no clear skew of results as indicated through the range‚ 14 and the error percentage‚ 161.47%‚ suggesting that the trials at this temperature were not very accurate as they were largely inconsistent. The 50oC also proved to have inaccuracies‚ however‚ not as significant as the previous temperature‚
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Lab Report The effect of temperature on the reaction between Catalase and H2O2 Sarah AlShemesi In this experiment we’ll be exploring the effects of temperature on the reaction between Catalase and H2O2.We’ll be using five different temperatures to test this. The five different temperatures will be 10‚ 30‚ 50‚ 70 and 90 oC. We will use the liver as a source of Catalase. A 1 gram piece of liver will be inserted into a test tube with 2 cm3 of water‚ then 2 cm3 of H2O2 will be added. The Catalase
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