30FRAAUTITA BELSWEDEU"DEN"CHE25GBRFINHUN"PRT ESPGRC, LUXNORJAPPOL"CZENLDSVNAUSUSA"NZLCANISLŠVK IRLISRCHLEST10KORМЕX5102030405060Total tax revenue (% of GDP)Line of best fit: Y = -1.52 + 0.61 XR? = 0.61Figure 7 Social expenditure in relation to total tax revenue for selected OECD countriesBased on OECD (2007)The graph in Figure 7 plots a variable Y against a variable X for 33 OECD countries using 2007 data.Variable Y is an indicator of the level of government social expenditure (as a proportion of GDP). VariableX is the level of government tax revenue (also as a percentage of GDP). Figure 7 also shows theregression equation for the line of best fit and the value of R2 which measures the strength ofassociation between X and Y. This question has two parts; please answer both part (i) and part (ii).i) Examine Figure 7 and select the statements which are correct. (Choose one or more answers)It is impossible to identify any linear relationship between the two variables from the graph.The graph reveals a positive linear association between the two variables.The graph suggests that an increase in social expenditure requires an increase in tax revenue.The graph does not suggest that an increase in tax revenue leads to lower social expenditure.ii) Using the regression equation, calculate the percentage point change in social expenditure (Change invariable Y) associated with a decrease in tax revenue (change in variable X) of 10 percentage points.(Note that, in this case, you should not express the percentage changes as decimals; use theunadjusted percentage figures.) Give your answer to two decimal places.% of GDPSocial expenditure (% of GDP)

From the given information, The line of best fit is, Y=-1.52+0.61X, R^2=0.61 Here, X represents the…

Answered: The graph in Figure 7 plots a variable…

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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RequiredPage 92 The company uses the number of professional hours as the cost driver for office support costs. Use an algebraic equation to describe how total office support costs can be estimated. Use a spreadsheet program to perform a regression analysis. Use office support costs as the dependent variable (Y) and the professional hours as the independent variable (X). Determine the total fixed cost per office and variable cost per professional hour. Identify the R2 statistic provided by the Excel program and explain what it means. Mr. Dean plans to open a new branch office in a Dallas suburb. He expects that the monthly professional hours will be 3,000. Estimate the total office support cost for Mr. Dean. What portion of the total cost is fixed and what portion is variable? Explain how multiple regression analysis could be used to improve the accuracy of the cost estimates. *You will use excel to setup a worksheet with your data and run regression analysis.*
Use the Financial database from “Excel Databases.xls” on Blackboard. Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company. Use Excel to develop the multiple linear regression model. Assume a 5% level of significance. Which independent variable is the strongest predictor of the average P/E ratio of a company? A. Total Revenues B. Average Yield C. Earnings Per Share D.Return on Equity E. Total Assets F.Dividends Per Share Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287…
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
Ariel was running analyses over and over in census data and came across a correlation between weight and debt (r=.78). Independent variable is weight and dependent variable is debt. b) Curious Ariel noted some statistics on these weight (M=160lb, SD=15lb) and debt (M=196k, SD=20k). If Ariel wanted to calculate a regression equation, what would her slope and intercept be?
Please answer the second question. Thank you.
Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…
In linear regression analysis, the coefficient for the x-variable when the y-variable is regressed on the x-variable can be thought of as: Note: more than one answer may be correct Group of answer choices How much the value of the predicted y-variable will change when the x-variable changes by one unit. In the simple (two variable) linear regression model, the coefficient can be thought as the slope coefficient that measures the responsiveness of y to changes in x. The estimated coefficient will change if the sample containing x and y changes. The sample coefficient is an estimate of the population coefficient Before interpreting the coefficient for the x-variable, we should test whether the coefficient is statistically significant.
One of the biggest changes in higher education in recent years has been the growth of online universities. The Online Education Database is an independent organization whose mission is to build a comprehensive list of the top accredited online colleges. The following table shows the retention rate (%) and the graduation rate (%) for 29 online colleges.a). Use Excel Data Analysis Tool – Regression to get the relationship between the two variables;b). Create a scatter diagram for the two variables and display regression equation and R square on chart, then explain the relationship between the variables;c). Did the estimated regression equation provide a good fit?d). Suppose you were the president of South University. After reviewing the results, would you be able to use the regression result for forecasting. College RR(%) GR(%) Western International University 7 25 South University 51 25 University of Phoenix 4 28 American InterContinental University 29 32 Franklin…
One year consumers spent an average of $22 on a meal at a resturant. Assume that the amount spent on a resturant meal is normally distributed and that the standard deviation is $3.Complete parts (a) through (c) below. a. What is the probability that a randomly selected person spent more than $24?

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