A model is built to explain the evolution of spending on tourism and recreation in a certain group offamilies (Y in USD/person/year). As potential explanatory variables are considered:X1average annual income per person in the family (in USD),X2 – number of people in the family,X3 – nature of employment of the head of householdIfX3=1, when the head of the family is self-employed,X3=0, when the head of the family is an employeeBased on the collected data, linear correlation coefficients between variables were calculated andobtained0,84R, = -0,47[1 -0,55 0, 62R=1-0,420,751Using Hellwig's method, select the optimal combination of explanatory variables for the tourism andrecreation expenditure model.

Given information: It is given that a model is built to explain the evolution of spending on tourism…

Answered: A model is built to explain the…

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Repeat Example 5 when microphone A receives the sound 4 seconds before microphone B.
If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
The scatterplot of these two variables reveals a potential outlying month when the average temperature is about 53◦F and average crawling age is about 28.5 weeks. (a) Does this point have high leverage? (b) Is it an influential point?
Suppose a researcher believes that the occurrence of natural disasters such as earthquakes leads to increased activity in the construction industry. he decides to collect province-level data on employment in the construction industry of an earthquake-prone country, like Japan, and regress this variable on an indicator variable that equals 1 if an earthquake took place in that province in the last five years. a. Should the researcher include province fixed effects in order to control for location specific characteristics of the labor market? b. What can the researcher to control for the location effects?
Consider the following variables: Y=daily productivity score (measured in points) X1=0 if undergraduate student,1 if graduate student X2=hours of sleep per night 1. If you want to test whether type of student modifies the association between hours of sleep per night and daily productivity score, which model (from attached image) should you consider and what is the null hypothesis for this test? A. Use Model 3 and test H0: β2=0 B. Use Model 5 and test H0: β3=0 C. Use Model 5 and test H0: β1=0 D. Use Model 5 and test H0: β2=0 E. Use Model 2 and test H0: β1=0 2. Suppose that you decide to use Model 5 (from pocture attached) to describe the relationship between type of student, hours of sleep per night, and daily productivity score. You use the method of least squares to obtain the following: Y= -0.5 + 3(X1) + 1.5(X2) + 2.5(X1X2) What is the estimated slope relating hours of sleep per night and daily productivity score among undergraduate students? A. 2 B. None of…
A manufacturer wants to optimize its shipment of goods to its customers. To minimize their turnover time and avoid building up stocks that add costs, the wholesaler wants to know if weather conditions are important in determining the type of shoe demanded. Specifically, he would like to know if high temperatures affect the sale of closed, rubber-heeled walking shoes. He the data showing the temperature recorded at the location of its retail shops, as well as their record of sales of goods, during each day of the past year. What type of analysis should he conduct? What variables should be considered? Explain.
A manufacturing firm, Caleb Corp, produces and sells product in its home (US) market, and in a foreign market. There is inherent risk in the revenues collected from the foreign market due to volatility in the exchange rate. Under a benchmark strategy, all of the production takes place in the home country. The resulting expected profits for Caleb Corp are variable, due to variation in the exchange rate. As an approximation, the firm has estimated profits for five possible ranges of the exchange rate, with profit represented as a lottery, L= (.2, 150; .2, 200; .3, 220; .2,250; .1, 270) The probabilities are estimated probabilities for the different ranges. The outcomes in this lottery are the estimated final profit levels (not changes in profit). (a) Calculate the expected profit if the firm follows this benchmark strategy, i.e., E(L)
A manufacturing firm, Caleb Corp, produces and sells product in its home (US) market, and in a foreign market. There is inherent risk in the revenues collected from the foreign market due to volatility in the exchange rate. Under a benchmark strategy, all of the production takes place in the home country. The resulting expected profits for Caleb Corp are variable, due to variation in the exchange rate. As an approximation, the firm has estimated profits for five possible ranges of the exchange rate, with profit represented as a lottery, L= (.2, 150; .2, 200; .3, 220; .2,250; .1, 270) The probabilities are estimated probabilities for the different ranges. The outcomes in this lottery are the estimated final profit levels (not changes in profit). Now suppose the firm can also buy forward contracts on foreign currency to neutralize the effect of the exchange rate on profits. Assume that these provide complete hedging, but that it involves an additional cost, so that following the…
The authors of a paper investigated whether water temperature was related to how far a salamander would swim and whether it would swim upstream or downstream. Data for 14 streams with different mean water temperatures where salamander larvae were released are given (approximated from a graph that appeared in the paper). The two variables of interest are x = mean water temperature (°C) and y = net directionality, which was defined as the difference in the relative frequency of the released salamander larvae moving upstream and the relative frequency of released salamander larvae moving downstream. A positive value of net directionality means a higher proportion were moving upstream than downstream. A negative value of net directionality means a higher proportion were moving downstream than upstream. Mean Temperature (x) Net Directionality (y) 6.12 −0.088.11 0.25 8.57 −0.1410.51 0.00 12.5 0.08 12.04 0.03 12.45 −0.0717.93 0.29 18.34 0.23 19.84 0.24 20.3 0.19 19.02 0.14 17.78 0.05 19.67…
The authors of a paper investigated whether water temperature was related to how far a salamander would swim and whether it would swim upstream or downstream. Data for 14 streams with different mean water temperatures where salamander larvae were released are given (approximated from a graph that appeared in the paper). The two variables of interest are x = mean water temperature (°C) and y = net directionality, which was defined as the difference in the relative frequency of the released salamander larvae moving upstream and the relative frequency of released salamander larvae moving downstream. A positive value of net directionality means a higher proportion were moving upstream than downstream. A negative value of net directionality means a higher proportion were moving downstream than upstream. Mean Temperature (x) Net Directionality (y) 6.12 −0.088.01 0.25 8.57 −0.1410.61 0.00 12.5 0.08 11.94 0.03 12.55 −0.0717.93 0.29 18.24 0.23 19.84 0.24 20.3 0.19 19.12 0.14 17.78 0.05 19.57…
The authors of a paper investigated whether water temperature was related to how far a salamander would swim and whether it would swim upstream or downstream. Data for 14 streams with different mean water temperatures where salamander larvae were released are given (approximated from a graph that appeared in the paper). The two variables of interest are x = mean water temperature (°C) and y = net directionality, which was defined as the difference in the relative frequency of the released salamander larvae moving upstream and the relative frequency of released salamander larvae moving downstream. A positive value of net directionality means a higher proportion were moving upstream than downstream. A negative value of net directionality means a higher proportion were moving downstream than upstream. Mean Temperature (x) Net Directionality (y) 6.22 −0.08 8.01 0.25 8.67 −0.14 10.61 0.00 12.5 0.08 11.94 0.03 12.55 −0.07 17.93 0.29 18.34 0.23…

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A model is built to explain the evolution of spending on tourism and recreation in a certain group of families (Y in USD/person/year). As potential explanatory variables are considered: X, – average annual income per person in the family (in USD), X2 – number of people in the family,