Answered: . An economist studies the relationship…

. An economist studies the relationship between the price (x) and weekly demand (y) of a certain product. Assume the SLR model utility test finds evidence of a linear relationship between price

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The table lists the cost in millions of dollars for a 30-second commercial for selected years. Year 1994 1998 2004 2008 2011 Cost 33.7 34.2 35.0 35.5 35.9 a. Find a linear function f that models the data. b. Estimate the cost in 2010 and compare the estimate to the actual value of $36.6 million. Did your estimate involve interpolation or extrapolation? a. Use linear regression to determine the equation of the line that best fits the data. The linear function is f(x) = (Type an expression using x as the variable. Use integers or decimals for any numbers in the expression. Round to three decimal places as needed.)
The number of banks in a country has been dropping steadily since 1984, and the trend in recent years has been roughly linear. The annual data for the years 1999 through 2008 can be summarized as follows, where x represents the years since 1990 and y the number of banks, in thousands. n=10 Ex-235 ²-5605 Ey-77.564 Ey²=603.80424 Exy-1810.155 a. Find an equation for the least squares line. b. Use your result from part a to predict the number of banks in the year 2020. c. If this trend continues linearly, in what year will the number of banks drop below 6200? d. Find and interpret the correlation coefficient.
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
Price elasticity of demand (supply) or simply elasticity of demand (supply) measures the relative or percentage variation experienced by the quantity demanded (supplied) as a consequence of a change in the price of one percent (1%); In other words, it measures the intensity with which buyers (sellers) respond to a change in the priceprice. Elasticity is often used with respect to the price-demand relationship or the price-supply relationship, but the applicability of this concept is not restricted to that single case, but is broader, since the elasticity is calculated in percentages, since it is the only way to obtain a common unit of measure. When calculating the elasticity in arelationship, the units of measurement are maintained, therefore, they do not measure a proportional change, but a propensity, such as the well-known propensit to Keynesian consumption. The rate at which the selling price changes and from a product, with respect to its supply "x", is given by the following…
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Which of the following statements best describes linear regression? A measure of the degree of dependence between two variables. A statistical technique using pairs of data and identifying a line which ‘best fits’ all of the pairs of observations. A measure of the proportion of changes in the dependent variable which can be explained by a change in the independent variable. Shows individual costs against their associated activity levels but makes no attempt to identify a linear relationship between them.
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An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Table 1 below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. Year JALSH (Y) CPI (X) 2006 0.41 4.7 2007 0.19 7.1 2008 -0.23 11.5 2009 0.32 7.1 2010 0.19 4.3 2011 0.03 5.0 2012 0.27 5.6 2013 0.21 5.7 2014 0.11 6.1 2015 0.05 4.6 2016 0.00 6.4 2017 0.21 5.3 The estimated regression…