Due in class Feb 6 UCI ID_____________________________ MultipleChoice Questions (Choose the best answer‚ and briefly explain your reasoning.) 1. Assume we have a simple linear regression model: . Given a random sample from the population‚ which of the following statement is true? a. OLS estimators are biased when BMI do not vary much in the sample. b. OLS estimators are biased when the sample size is small (say 20 observations)
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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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considers the relationship between two variables in two ways: (1) by using regression analysis and (2) by computing the correlation coefficient. By using the regression model‚ we can evaluate the magnitude of change in one variable due to a certain change in another variable. For example‚ an economist can estimate the amount of change in food expenditure due to a certain change in the income of a household by using the regression model. A sociologist may want to estimate the increase in the crime rate
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REGRESSION ANALYSIS (SIMPLE LINEAR REGRESSION) Submitted By Maqsood Khan MS - MANAGEMENT SCIENCES‚ 2nd SEMESTER Submitted TO GOHAR REHMAN ASSISTANT: PROFESSOR‚ SUIT Sarhad University Of Science And Information Technology Peshawar SESSION: 2012-13 TABLE OF CONTENTS |S. No. |Subjects |Page No. | |1 | |Introduction
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1. Calculate real GDP for 2004 and 2005 using 2004 prices. To calculate the real GDP we use the constant price for 2004 which was $20. Real GDP (base year 2004) 2004 ($20 per CD x 100 CD’s) + ($110 per racquet x 200 racquets) = 24000 2005 ($20 per CD x 120 CD’s) + ($110 per racquet x 210 racquets) = 25500 By what percentage did real GDP grow? Because the Real GDP was $24000 in 2004 and $25500 in 2005‚ real GDP grew by ($25500 - $24000) / $24000 = 0.0625 or 6.25% 2. Calculate the
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Housing Prices in Blowing Rock‚ NC: A Hedonic Analysis Thomas Carter Economics 4000 1. Introduction A difficult characteristic to understand about the housing market is how a price is given for a particular house. That price will be designated to that particular house alone. All houses have various pricing‚ so I can’t always assume that one will cost more or less than any other. The pricing for houses vary based on their characteristics. Each characteristic must be analyzed to determine
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Introduction to Linear Regression and Correlation Analysis Goals After this‚ you should be able to: • • • • • Calculate and interpret the simple correlation between two variables Determine whether the correlation is significant Calculate and interpret the simple linear regression equation for a set of data Understand the assumptions behind regression analysis Determine whether a regression model is significant Goals (continued) After this‚ you should be able to: • Calculate and
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REGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. It does not‚ necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits‚ correlation does not tell us which variable is the cause and which‚ the effect. For example‚ the demand for a commodity and its price will generally be found to be correlated‚ but the question whether demand depends on price or vice-versa; will not be answered
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Simple Linear Regression Model 1. The following data represent the number of flash drives sold per day at a local computer shop and their prices. | Price (x) | Units Sold (y) | | $34 | 3 | | 36 | 4 | | 32 | 6 | | 35 | 5 | | 30 | 9 | | 38 | 2 | | 40 | 1 | | a. Develop as scatter diagram for these data. b. What does the scatter diagram indicate about the relationship between the two variables? c. Develop the estimated regression equation and explain what the
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Introduction This presentation on Regression Analysis will relate to a simple regression model. Initially‚ the regression model and the regression equation will be explored. As well‚ there will be a brief look into estimated regression equation. This case study that will be used involves a large Chinese Food restaurant chain. Business Case In this instance‚ the restaurant chain ’s management wants to determine the best locations in which to expand their restaurant business. So far the most
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