The sales of a company for the last cight years are given below : 1987 52 1988 1989 45 - 98 Estimate sales figure for 1995 using an equation of the form Y = ab* where X= years and Y= sales. Year 1990 1991 1992 Sales ('000) : 1993 175 1994 220 92 110 185
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- Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?The rate of increase of COVID-19 infection is directly proportional to the number of people infected and to the number people not yet infected. An isolated remote barangay of population 10,000 records its first case on June 15, 2020. After two days, 100 people are infected. Develop a model that predicts the number of COVID-19 cases in the barangay. How long will it take for 90% of the population to be infected? Assume that the virus persists in the person infected.The least-squares regression equation is y=728.0x+14,705 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.8165. For every dollar increase in median income, the percent of adults having at least a bachelor's degree is ___%, on average. For a median income of $0, the percent of adults with a bachelor's degree is ____%.
- Given: A regression of ln(wage) on educ, exper, exper2, female, married, numdep and two interaction terms female ∗ edu and female ∗ married. (For the interaction terms I multiplied female data x edu data and so forth) Question: What does the coefficient on the interaction term measure? Interpret the coefficients on the interaction term, female ∗ edu and female ∗ married.The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Predict the median income of a region in which 30% of adults 25 years and older have at least a bachelor's degree.Accountants at the Tucson firm, Larry Youdelman,CPAs, believed that several traveling executives were submittingunusually high travel vouchers when they returned from businesstrips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regres-sion equation relating expected travel cost to number of days on the road ( x1 ) and distance traveled ( x2 ) in miles:yn = +90.00 + +48.50x1 + +.40x2The coefficient of correlation computed was .68.a) If Donna Battista returns from a 300-mile trip that took herout of town for 5 days, what is the expected amount she shouldclaim as expenses?b) Battista submitted a reimbursement request for $685. Whatshould the accountant do?c) Should any other variables be included? Which ones? Why?
- The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Interpret the slope.a) Find the value of X, Y, Z b) Calculate the composite Index for the cost of making the food in the year 2017 based on the year 2015.Women in the Workforce The following table givesthe number of women age 16 years and older (inmillions) in the U.S. civilian workforce for selectedyears from 1950 and projected to 2050.a. Use x as the number of years past 1950 to create acubic model using these data.b. During what year does the model indicate that thenumber of women in the workforce will reach itsmaximum?
- The least-squares regression equation is y=647.8x+17,858 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7507. predict the median income of a region in which 20% of adults 25 years and older have at least a bachelor's degree. Round to the nearest dollar as needed.Say you have a regression where you are regressing wages on several variables, one being Years of Education (X1). In this regression, you estimate βˆx1 = 1.5 and it is statistically significant. Suppose you then find there is information of individuals SAT scores (an approximate measure of underlying ability) and add it to your regression as X2. You now get that βˆx1 = 0.5 and is still statistically significant, and you get βˆx2 = 0.1 and it is also statistically significant. What type of relationship to you suspect there is between Years of Education, SAT scored, and wages? Touch on the correlation of each variable to every other variable and explain the likely causal pathways. If cor(x1, y) ≡ 0.5, and cor(x2, y) ≡ 0.5, explain when regressing y on x1 and x2 gives an R2 of 0.5A college bookstore must order books two months before each semester starts. They believe that the number of books that will ultimately be sold for any particular course is related to the number of students registered for the course when the books are ordered. They would like to develop a bestfitting line to predict how many books to order. From past records, the bookstore obtains the number of students registered, X, and the number of books actually sold for a course, Y , for 12 different semesters.A scatterplot of the data along with the best fitting line is presented below. a. The correlation between the two variables is r = .89. Calculate and interpret the value of r2.b. The equation for the best fitting line is Y = 9.30 + 0.673X. Explain and interpret the value of 9.30.c. How many books should the store order for a class of 50 students? Would you trust this prediction?
