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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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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Project 1: Linear Correlation and Regression Analysis Gross Revenue and TV advertising: Pfizer Inc‚ along with other pharmaceutical companies‚ has begun investing more promotion dollars into television advertising. Data collected over a two year period‚ shows the amount of money Pfizer spent on television advertising and the revenue generated‚ all on a monthly bases. |Month |TV advertising |Gross Revenue | |1 |17 |4.1 | |2
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these characteristics and modeled the relationship between them and the price of real estate for a specific area. How are these characteristics used in determining the price? A model that is commonly used in real estate appraisal is the hedonic regression. This method is specific to breaking down items that are not homogenous commodities‚ to estimate value of its characteristics and ultimately determine a price based on the consumers’ willingness to pay. The approach in estimating the values is done
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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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CHAPTER 4 – THE BASIS OF STATISTICAL TESTING * samples and populations * population – everyone in a specified target group rather than a specific region * sample – a selection of individuals from the population * sampling * simple random sampling – identify all the people in the target population and then randomly select the number that you need for your research * extremely difficult‚ time-consuming‚ expensive * cluster sampling – identify
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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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STATISTICS FOR MGT DECISIONS FINAL EXAMINATION Forecasting – Simple Linear Regression Applications Interpretation and Use of Computer Output (Results) NAME SECTION A – REGRESSION ANALYSIS AND FORECASTING 1) The management of an international hotel chain is in the process of evaluating the possible sites for a new unit on a beach resort. As part of the analysis‚ the management is interested in evaluating the relationship between the distance of a hotel from the beach and the hotel’s
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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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LINEAR REGRESSION MODELS W4315 HOMEWORK 2 ANSWERS February 15‚ 2010 Instructor: Frank Wood 1. (20 points) In the file ”problem1.txt”(accessible on professor’s website)‚ there are 500 pairs of data‚ where the first column is X and the second column is Y. The regression model is Y = β0 + β1 X + a. Draw 20 pairs of data randomly from this population of size 500. Use MATLAB to run a regression model specified as above and keep record of the estimations of both β0 and β1 . Do this 200 times. Thus you
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