Example 7.12: The following forecasting equation has been derived by a least-squares method: ŷ =10.27 + 1.65x (Base year:1992; x = years; y = tonnes/year) Rewrite the equation by (a) shifting the origin to 1997. (b) expressing x units in months, retaining yn tonnes/year. (c) expressing x units in months and y in tonnes/month.
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- Please answerSuppose you wanted to estimate the effect of being educated on being in the labor force. You estimate a model with two variables, LF is a binary variable = 1 if the person is participating in the labor force and the variable educ measures the number of years of education a person has received. You get the following estimated regression: LF = 0.1 + 0.15educ Which of the following is the correct interpretation about the effect of an additional year of education? O A 1% increase in education increases the number of those participating in the labor force by 15 percentage points. A additional year in education increases the number of those participating in the labor force by 0.15 percentage points A additional year in education increases the number of those participating in the labor force by 0.15% An additional year of education increases the probability of participating in the labor force by 15 percentage points. An additional year of education increases the probability of participating…The lecturer is interested to see what variables, if any will help determine the number of hours spent on studying statistics. Test and find any regression models that can help determine the number of hours spent on studying. (Hint run Study hrs. on…)(a) On average, how much do males study more(less) than females?(b) Do people who enjoy the Big Bang Theory impact on the number of hours studies?(c) Is age a determining factor on the number of hours studied?(d) Do students with a stronger math background study more or less? Also state how much more or less Answer all questions.. Quiz Results EQR Study Hrs Age Sex BBT MB MC AuHS LM 15 10 3 19 0 0 1 1 0 1 14 15 4 24 0 0 1 0 0 1 9 15 1 20 0 10 1 0 0 1 6 10 3 21 0 0 1 1 0 1 14 15 4 21 0 9 1 0 0 1 12 10 6 21 0 2 0 1 0 1 12 13 2 21 1 8 1 0 0 0 15 15 0 20 0 8 1 0 0 1 12 15 3 20 0 10 1 0 0 1 13 15 0.2 19 0 8 1 0 0 1 15 15 2 20 0 6 1 0 1 1 12 14 5 20 0 5 1 1 1 1 14 15 7 22 0 8 0 0 0 0 7 7 10 21 1 7 0 0 1 0 11 15…
- pan's high population density has resulted in a multitude of resource-usage problems. One especially serious difficulty concerns waste removal. An article reported the development of a new compression machine for processing sewage sludge. An important part of the investigation involved relating the moisture content of compressed pellets (y, in %) to the machine's filtration rate (x, in kg-DS/m/hr). The following data was read from a graph in the article. x 125.8 98.1 201.4 147.3 145.9 124.7 112.2 120.2 161.2 178.9 159.5 145.8 75.1 151.5 144.2 125.0 198.8 133.9 y 77.9 76.8 81.5 79.8 78.2 78.3 77.5 77.0 80.1 80.2 79.9 79.0 76.9 78.2 79.5 78.1 81.5 71.0 (a) Determine the slope and intercept of the estimated regression line. (Round your answers to 5 decimal places, if needed.)slope: intercept: (b) Does there appear to be a useful linear relationship? Carry out a test using the ANOVA approach and a significance level of 0.05. State the appropriate null and alternative hypotheses.…An engineer creates a model to predict the electric consumption of a household in summer in a day with a predictor variable of the number of hours the air-conditioner is running. The electric consumption is only at 26 kWh per day if aircon is not used. If the aircon was used by 1 hr, the electric consumption would increase by an additional 1.44 kWh. Find the average electric consumption if the aircon is used 15 hrs.Listed below are the numbers of cricket chirps in 1 minute and the corresponding temperatures in °F. Find the regression equation, letting chirps in 1 minute be the independent (x) variable. Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute, using the regression equation. What is wrong with this predicted temperature? Chirps in 1 min Temperature (°F) 913 1086 969 1081 1249 1138 1153 850 78.9 82.2 79.6 86.3 92 90.8 88 68.1 C The regression equation is y = + (x. (Round the y-intercept to one decimal place as needed. Round the slope to four decimal places as needed.)
- 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.Suppose the following estimated regression equation was determined to predict salary based on years of experience. Estimated Salary = 29,136.63 +2257.51(Years of Experience) What is the estimated salary for an employee with 24 years of experience? Answer Keypad Keyboard Shortcuts TablesDescribe three approaches to modeling seasonality in a regression forecast.
- Consider the sample regression equation that predicts the calorie content in a hamburger (in cals) using the fat content (in grams) yi = 310+14.4 (fati) + ei Which of the following statements is correct regarding the estimated equation? a) a. the equation is expressing a non-linear relationship between fat and calories b) b. a hamburger with 310 calories has zero fat content c) c. a hamburger’s calorie content rises by about 14.4 grams for every additional gram of fat d) d. the ei is called the stochastic error term, and is a representation of those factors that cause fat content that the regression is not accounting forlakhs) of a certain commodity for the year On the basis of quarterly sales (in 2008-12, the following calculations were made : Trend: Y = 20 + 0.5 t with origin at 1st quarter of 2008. where 1 = time unit = one quarter and y = quarterly sales ( Seasonal variations: Quarter I II III IV Seasonal Index 80 90 120 110 Estimate the quarterly sale for the year 1979 using multiplicative model.An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Table 1 below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. Year JALSH (Y) CPI (X) 2006 0.41 4.7 2007 0.19 7.1 2008 -0.23 11.5 2009 0.32 7.1 2010 0.19 4.3 2011 0.03 5.0 2012 0.27 5.6 2013 0.21 5.7 2014 0.11 6.1 2015 0.05 4.6 2016 0.00 6.4 2017 0.21 5.3 The estimated regression…