Concept explainers
If epidemics are identified with solution trajectories in which the number of infected individuals initially increases, reaches a maximum, and then decreases, use a nullclineanalysis to show that an epidemic occurs if and only if
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- Consider the Keynesian consumption function Yt = B₁ + B₂x2t + &t where yt is per capita consumption, and x2+ is per capita income. The coefficient ₂ is interpreted causally as the marginal propensity to consume, and we expect 0arrow_forwardAssume that we have the usual Simple Linear Regression model given by: Y₁ = Bo + Bixi +8 Show that in this case: Where Txy R² = rzy is the correlation coefficient between x and y.arrow_forwardConsider the regression model Y₁ = BX; +u; Y Where ui and X; satisfy the assumptions specified here. Let ẞ denote an estimator of ẞ that is constructed as ẞ = Show that ẞ is a linear function of Y₁, Y2,..., Yn. Show that ẞ is conditionally unbiased. 1. E (YiX1, X2,..., Xn) = == X + +Yn) 2. E(B|×1, X2,..., Xn) = E = B Χ | (X1, X2,..., Xn) = where Y and X are the sample means of Y; and X;, respectively.arrow_forwardA 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: X1 average annual income per person in the family (in USD), X2 – number of people in the family, X3 – nature of employment of the head of household If X3=1, when the head of the family is self-employed, X3=0, when the head of the family is an employee Based on the collected data, linear correlation coefficients between variables were calculated and obtained 0,84 R, = -0,47 [1 -0,55 0, 62 R= 1 -0,42 0,75 1 Using Hellwig's method, select the optimal combination of explanatory variables for the tourism and recreation expenditure model.arrow_forwardHeights (om) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 138 to 188 cm and weights of 41 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x 167.74 cm, y 81.46 ko, r0.239, Pvalue 0.017, and y - 106 + 1,15x. Find the best predicted value of y (weight) given an adult male who is 153 cm tall. Use a 0.01 significance level. The best predicted value of y for an adult male who is 153 cm tall is kg. (Round to two decimal places as needed.)arrow_forwardLet A and B represent two variants (alleles) of the DNA at a certain locus on the genome. Assume that 40% of all the alleles in a certain population are type A and 30% are type B. The locus is said to be in Hardy-Weinberg equilibrium if the proportion of organisms that are of type AB is (0.40)(0.30) = 0.12. In a sample of 300 organisms, 42 are of type AB. Can you conclude that this locus is not in Hardy-Weinberg equilibrium?arrow_forwardLet A and B represent two variants (alleles) of the DNA at a certain locus on the genome. Assume that 40% of all the alleles in a certain population are type A and 30% are type B. The locus is said to be in Hardy-Weinberg equilibrium if the proportion of organisms that are of type AB is (0.40)(0.30) = 0.12. In a sample of 300 organisms, 43 are of type AB. Can you conclude that this locus is not in Hardy- Weinberg equilibrium? Find the P-value and state a conclusion. Round the answer to four decimal places. The P-value is We (Click to select) conclude that the locus is not in Hardy-Weinberg equilibrium.arrow_forwardSuppose you estimate a regression equation Income = α + β1Experience + β2Business + β3Gender + β4Private + β5Experience*Gender + ε Income - annual income is in thousands of dollars (1 unit of income = $1000);Experience is in years;Business is a dummy variable set to 1 if person has a business degree, 0 otherwise;Gender is a dummy variable set to 1 for females, 0 for males;Private is a dummy variable set to 1 if a person attended private college, 0 otherwise; The data are on individuals who graduated from college within last 10 years. 1.) A. Use information from Question 1 . What is the average income of males with non-business degree, who went to public college, and who have 3 years of experience? (to 3 decimal points) B. Use information from Question 1 What is the average income of females with non-business degree, who went to public college, and who have 6 years of experience? (to 3 decimal points) C. Use information from Question 1. Which of the following statements is a correct…arrow_forwardHow might the competitive-hunter model be validated? Include adiscussion of how the various constants a, b, m, and n might beestimated. How could state conservation authorities use the modelto ensure the survival of both species?arrow_forwardQ2.A study was conducted to optimize the concentration temperature in relation to the amount of solids content (g/L) of orange concentrate (treatments). Due to limited number of evaporators available, the experimenter was forced to use 4 different sized evaporators. It was presumed that the size of the evaporators could be a possible source of variation (columns). As each run took 4 days time, it was decided to control the effect of the experimentation time (rows) and the experiment was conducted in a Latin Square Design. Answer the following questions: What will be the layout of this design ii. Write the ANOVA showing the first two columns only (i.e. SOV and degrees of freedom) iii. Consider orange concentrate as treatments and time as a blocking factor (RCBD) by ignoring evaporator effect, Write the layout of this design iv. By considering (iii) make ANOVA showing only the first two columns i.arrow_forwardThe following data shows the atmospheric pollutants yi(relative to an EPA standard) at half hour interval xi. Find the equation y=a+bx of the least square line that best fits the data points given by 2,1, 5,2, 7,3, 8,3. Hence predict the atmospheric pollutant at x=6 half hour.arrow_forward3b. A linear regression yields R2 = 0. Does this imply that βˆ1 = 0?arrow_forwardarrow_back_iosSEE MORE QUESTIONSarrow_forward_ios
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