Questions 2-4 are based on the following information: Consider the following population model for household consumption: cons= a Binc+ Bzeduc +B,hhsize + u, where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. 2. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on inc, educ, and hhsize. One can a) be certain that the R2 is equal to 1 b) be certain that the R2 is equal to 0 c) be certain that the R2 is less than 1 but greater than 0. d) not be certain 3. Suppose that the variable for consumption is measured with error, so conss = cons + e, where conss is the mismeaured variable, cons is the true variable, e is random, i.e., e independent of all the regressors. We would expect that: a) OLS estimators for the coefficients will all be biased b) OLS estimators for the coefficients will all be unbiased c) all the standard errors will be bigger than they would be without the measurement error

Questions 2-4 are based on the following information: Consider the following population model for household consumption: cons= a Binc+ Bzeduc +B,hhsize + u, where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. 2. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on inc, educ, and hhsize. One can a) be certain that the R2 is equal to 1 b) be certain that the R2 is equal to 0 c) be certain that the R2 is less than 1 but greater than 0. d) not be certain 3. Suppose that the variable for consumption is measured with error, so conss = cons + e, where conss is the mismeaured variable, cons is the true variable, e is random, i.e., e independent of all the regressors. We would expect that: a) OLS estimators for the coefficients will all be biased b) OLS estimators for the coefficients will all be unbiased c) all the standard errors will be bigger than they would be without the measurement error

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Description: #3 Questions 2-4 are based on the following information:Consider the following population model for household consumption:cons= a Binc+ Bzeduc +B,hhsize + u, where cons is consumption, inc is income, educis the education level of household head, hhsi

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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Consider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certain
Question 18 At a local club, the ages of the members and the times they took to run a 10 km race are recorded. For a random sample of 25 club members aged between 27 and 60, their ages (x years) and times (y minutes) produce the following regression line. y = 0.83x + 41.28Four new members join the club. Their respective ages (in years) are 26, 18, 22, and 28. When the respective race times for the 4 new members are estimated, which one of these estimated race times is the most reliable?A. 62.86 minutesB. 56.22 minutesC. 59.54 minutesD. 64.52 minutes
Question 18 At a local club, the ages of the members and the times they took to run a 10 km race arerecorded. For a random sample of 25 club members aged between 27 and 60, their ages(x years) and times (y minutes) produce the following regression line. y = 0.83x + 41.28Four new members join the club. Their respective ages (in years) are 26, 18, 22, and 28. When therespective race times for the 4 new members are estimated, which one of these estimated race timesis the most reliable?A. 62.86 minutesB. 56.22 minutesC. 59.54 minutesD. 64.52 minutes Question 19 The data of the number of ‘centuries’ i.e. a scores of 100 runs or more, scored by players at acricket club during a season are given in the following table.Number of centuries Number of players0 41 k2 33 24 38 1Given that the mean number of centuries scored per player is 1.95, find the value of k.A. 7B. 3C. 4D. 1 Question 20The asking prices (in Rands) and the actual selling prices (in Rands), after bargaining, of 8commodities are…
question 32 Statistics students in Oxnard College sampled 10 textbooks in the Condor bookstore and recorded the number of pages in each textbook and its cost. The bivariate data are shown below: Number of Pages (xx) Cost(yy) 575 95.25 351 60.65 788 137.2 600 108 393 75.95 897 155.55 504 76.6 571 86.65 516 79.4 986 166.9 A student calculates a linear modely = __________x +_____________ . (Please show your answers to two decimal places)Use the model to estimate the cost when number of pages is 829.Cost = $___________- (Please show your answer to 2 decimal places.)
Question #6 Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude 4 8 14 24 27 31 32 Temperature 55 37 20 −5 −27 −41 −57 a. Find the explained variation. ______________ (Round to two decimal places as needed.) b. Find the unexplained variation. _______________ (Round to five decimal places as needed.) c. Find the indicated prediction interval. _____________°F < y < ____________ °F (Round to four decimal places as needed.)
question 2 Shown below are the scatterplots and results of three linear regression analyses done that relate several different behavioural traits to one another in crabs, taken directly from a published paper. The dashed line in each is the line of best fit (least squares regression line). The fitted regression equation, r-value and p-value for each analysis are given in the figure legend below the graphs. Relationships among personality traits in the swimming crab Portunus trituberculatus. Each data point represents an individual crab; data are shown as the specific valye of personality traits (n=88). (A) Relationship between boldness and activity (y=36.04x-17.572, r=0.459, P=0.00). (B) Relationship between activity and hesitancy (y=-0.152x+3.37, r=0.305, P=0.00). (C) Relationship between boldness and hesitancy (y=-1.18x+7.07, r=0.158, P=0.02) For each graph (A – C) and the corresponding results in the figure caption above (A – C), comment on whether the result indicates the null…
Section 10.3 Question #6 Listed below are altitudes (thousands of feet) and outside air temperatures (°F) recorded during a flight. Find the (a) explained variation, (b) unexplained variation, and (c) indicated prediction interval. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 95% confidence level with the altitude of 6327 ft (or 6.327 thousand feet). Altitude 4 11 14 20 28 31 34 Temperature 55 39 26 −2 −34 −41 −59 a. Find the explained variation. ______________ (Round to two decimal places as needed.) b. Find the unexplained variation. _______________ (Round to five decimal places as needed.) c. Find the indicated prediction interval. _____________°F < y < ____________ °F (Round to four decimal places as needed.)
Question 2: The estimated regression equation for a model involving two independent variables and 65 observations is: yhat = 55.17+1.1X1 -0.153X2 Other statistics produced for analysis include: SSR = 12370.8, SST = 35963.0, Sb1 = 0.33, Sb2 = 0.20.a. Interpret b1 and b2 in this estimated regression equation b. Predict y when X1 = 65 and X2 = 70. c. Compute R-square and Adjusted R-Square. d. Comment on the goodness of fit of the model. e. Compute MSR and MSE. f. Compute F and use it to test whether the overall model is significant using a p-value (α = 0.05). g. Perform a t test using the critical value approach for the significance of β1.Use a level of significance of 0.05. h. Perform a t test using the critical value approach for the significance of β2.Use a level of significance of 0.05.
A researcher notes that, in a certain region, a disproportionate number of software millionaires were born around the year 1955. Is this a coincidence, or does birth year matter when gauging whether a software founder will besuccessful? The researcher investigated this question by analyzing the data shown in the accompanying table. Complete parts a through c below. a. Find the coefficient of determination for the simple linear regression model relating number (y) of software millionaire birthdays in a decade to total number (x) of births in the region. Interpret the result. The coefficient of determination is 1.___? (Round to three decimal places as needed.) This value indicates that 2.____ of the sample variation in the number of software millionaire birthdays is explained by the linear relationship with the total number of births in the region. (Round to one decimal place as needed.) b. Find the coefficient of determination for the simple linear regression model…
Question Six The following table gives the experience (in years) for several brokers and their number of stocks sold during the previous three months in the Egyptian stock market. Broker Experience ( in years) 4 12 9 6 10 16 7 Number of stocks 19 42 28 31 39 35 21 Determine both dependent and independent variables, and explain the expected relationship between Calculate the correlation coefficient comment on the Estimates the simple regression model and comment on the estimated Predict the number of stocks sold during the past three months by broker with eleven years of Without any calculation, If independent variable is divided over 3, what will be the effect on the estimated coefficients. Justify your
QUESTION 3 The Research Unit for Cecilion Supermart conducted an experiment to estimate the strength of thecarrier bag from the starch-based biofilms made from two different jicamas (sengkuang) of type Aand type B. However, the researcher claims that jicama type A produces more strength comparedto type B. To support this claim, 10kg weight item was put into 100 carrier bags made from jicamatype A and 200 carrier bags made from jicama type B were randomly selected. As a result, 8 bagsfrom jicama type A burst while 12 bags from jicama type B burst. Calculate a 95% confidenceinterval for the difference in true proportion of the carrier bags which burst between jicama type Aand type B. Give comment on the parameter estimate.
Question 5: A college is interested in if the year of receiving high-level education (college and above) influences students’ salaries when they join the working field. The college randomly selected 4 students who recently received a full- time work offer and collected their year of receiving high-level education and salary per week. The raw data is: Participant Year of high-level education Salary per week Participant 1 4 1150 Participant 2 5 1300 Participant 3 7 1600 Participant 4 2 750 Plot the scatterplot and label the participants. Calculate the correlation coefficient between the year of high-level education and salary per week. Calculate the regression equation using the year of receiving high-level education to predict the salary per week. If a student graduate from college and graduate school in a total of 6 years, what is this student’s predicted salary per week?